ABSTRACT. As part of my post-doctoral research into the effects of Artificial Intelligence (AI) on police work, I took an interest in camera operators to understand how algorithmic processes modify representations of delinquency phenomena. Thus, I spent 12 days under non-participant observator in the camera room, with the 19 men and 4 women of the Center of Video Supervision of a town in eastern France. In this paper, I will begin by examining the social characteristics of the actors I met: both those of the group surveyed and my own as a researcher. The “image hunters” are white, male, from the region, prior experience in law enforcement, fathers of families, working in a profession “without contact with the world” (Thomas, 48). My personal and professional characteristics - holder of a doctorate in a discipline unfamiliar to operators, Greek with a “Belgian accent” (Samuel, 38), living in Nantes while conducting a survey in the east of the country, single and childless - placed me as an outsider to the establishment's norms and profiles. These elements will be analyzed in order to better understand the conditions under which the survey took place, as well as the multiple distances of class, gender, nationality, lifestyle and political ideology that shaped the encounter between their world and mine (Darmon 2005; Rolle 2017). Secondly, I will focus on my efforts to create a common ground with my respondents (Beaud, Weber 2003) despite these discrepancies. Introduced to the operators by the manager and his deputy, I had to implement survey techniques aimed at distinguishing myself from management and reducing the distance with them. By analyzing my field notes, I distinguish my strategies into two categories, corresponding to two phases of the investigation: those deployed during the first meeting and those mobilized once the first contact had been established.

ABSTRACT. Drawing from my illness story, developing in two Oncological Institutes and marked by an initial misdiagnosis which hindered adequacy of therapies for two years, I reflect on what kind of self and autoethnography I could express and carry out, in the double agency of patient and STS researcher. Namely, a patient drawing on the repertoires, languages and frames of STS, and on my experience as ethnographer of sociotechnical artefacts and information infrastructures (Pellegrino, 2003, 2014). The relationship with ‘others’ (doctors, technicians, nurses, other patients and the wide assembly of human-non human entanglements in clinical practice) was ineludibly framed by this (half spontaneous half deliberate) positionality. In light of my being a patient-STS researcher, my autoethnographic ‘I’ is literally embodied/performed, and has a double soul, evocative (Ellis and Bochner, 2016) and analytic (Anderson, 2006). It is even more embodied than in autoethnography as such (see Spry, 2001), since in illness and consequent medicalization the body claims its own deep-rooted and unique voice, often forgotten and neglected otherwise. In my experience, even if connected to autobiography, autoethnography is different as more focused, thicker in description, contingent and time-space bound to vulnerability. Then my ‘I’ is performative, as trans-formative of my own illness trajectory (I consider my STS background crucial to avoid the bad end of the story). Being absorbed by the aim of positioning myself as an informed and competent participant, a “not naïve patient” (Pellegrino, 2021), struggling to make sense of inconsistencies and wounds, I tried to intervene and reshape my illness trajectory, sometimes with problematic and conflictual consequences as in the forced exit from the first Oncological Institute. Eventually, a performative ‘I’ is continuously re-forming the narrative restitution of the field, which enacts and selects different portions of this ‘I’, also in the present contribution, making it anew.

ABSTRACT. My mother lived with my family during her early years with dementia and I accompanied her to every appointment. Seeing all that was no longer deemed available to her made me want to understand more about the structural, institutional and social conditions that influenced her quality of life. I wanted better for her and every person touched by dementia. This experience as a care partner nudged me into pursuing a doctoral program. A week before my first class in social theory and five months into the COVID-19 pandemic, my mother’s health declined and I moved her into a long-term care (LTC) home. Restrictions prohibiting visitors meant I was limited to watching from the lobby as she disappeared down the hall, a social worker wheeling her to her room where she would spend the next two weeks in isolation. When visiting restrictions finally eased to allow “essential” caregivers to visit, we were shocked to realize that my ten-year-old daughter was not considered as such. For months, she and my mother connected through a patchwork of Zoom calls, mailed love notes, photos and artwork. When my daughter was finally permitted to visit, we waited anxiously in the corridor of the LTC home, my daughter asking curiously, “why are there no other kids here?” This question hung in the air throughout our visits, all the while seeing residents faces light up upon seeing a child. My mother and daughter were shining stars to each other, providing enormous inspiration for my research that explores relationships between people living with dementia in a LTC home and adolescents. This paper, and the digital story that my mother, daughter and I co-created, reveal how the theoretical framing and methodology for my research is shaped by my lived experience of engaging in my mother and daughter’s relationship.

ABSTRACT. The research critically reflects on gendered experiences in urban public space, focusing on street harassment. A qualitative methodology with a critical-case design was implemented, combining autoethnography and semi-structured interviews, including photo elicitation. Drawing on Bourdieusian theory and feminist epistemologies, this study highlights how symbolic violence, spatial exclusions, and neoliberal security policies shape uneven access to urban environments. The choice of qualitative methods aims to move beyond an incident-based approach to harassment (Fileborn & O’Neill, 2023) to explore women’s lived experiences – where the word «woman» used hereby is rooted in the trans-inclusive conceptualization proposed by Jenkins (2016). Autoethnography allows firsthand engagement with the embodiment and production of spatial meanings (Gale & Wyatt, 2019), offering insights from the researcher’s own social location. As Crawley (2012) notes, «I write autoethnography because I am commonplace» (p. 154). Relatedly, while Ellis and Bochner (1996) challenge accusations of self-indulgence, concerns about solipsism (Butz & Besio, 2009; Atkinson, 2006) were addressed by incorporating other voices through interviews, as suggested by Bassetti (2021). Ethical considerations were central to this study. Autoethnographic relationships move along a continuum from “researcher-and-researched” to “researcher-as-researched” (Doloriert & Sambrook, 2009), posing challenges of anonymity and disclosure. Consequentially, Medford’s (2006) concept of “mindful slippage” guided reflections on personal exposure. Self-reflection has been realized alongside positionality considerations, keeping these considerations in mind. My feminist political commitment and academic interest in gender and power inform my «situated knowledge» as a «partial, locatable, critical» perspective (Haraway, 1988, p. 584), shaped by my position as a white, Italian, cis, able, working-class, educated young woman. Lastly, this study demonstrates how feminist autoethnography can work to challenge dominant narratives on public space, gendered violence, and safety. Findings reveal that mainstream security policies, rooted in neoliberal control, contrast with feminist and community-led redefinitions of safety as relational and collective.

ABSTRACT. In recent decades, reflections on the role of the researcher in sociological inquiry have grown increasingly complex, partly due to approaches such as autoethnography. The concept of the researcher-activist in urban spaces has gained prominence, highlighting the integration of ethnographic methodologies, political engagement, and field activism (Martínez, 2023). This shift moves from an introspective “I-on-myself” perspective to a collective “we-on-ourselves” approach, emphasizing relational networks and the communal dimension of sociological practice. This research examines the self-positioning, stabilization, and destabilization strategies employed by researcher-activists in urban contexts, maintaining scientific rigor and neutrality. It draws on two theoretical perspectives: autoethnography (Ellis, Adams, & Bochner, 2011), which underscores methodological reflexivity and personal involvement, and public sociology (Burawoy, 2005) alongside activist scholarship (Hale, 2008), which fosters direct engagement with social movements. Despite their distinct emphases, these perspectives converge in recognizing the relational and political nature of social research. 1. How do researcher-activists navigate pressures on the one hand from political movements and resistance collectives, particularly when ideological boundaries remain more strict, on the other hand from academic institutions with respect to the institutional but free status of scientific research? 2. How does the collective dimension of “we” materialize and evolve in research practice? The study employs qualitative methods, including in-depth interviews with ten researcher-activists from diverse disciplines, working across five social contexts in Italy (Naples, Rome) and France (Lyon, Marseille, Paris), complemented by participant observation. Through a multi-sited ethnographic approach (Marcus, 1995), it explores how researcher-activists’ positioning adapts to political and cultural landscapes. By integrating autoethnographic reflexivity with the activist researcher’s collective engagement, this study critically examines the epistemological and ethical dilemmas inherent in politically engaged scholarship. Concluding in October 2025, it seeks to contribute to international debates on qualitative methods, representation, and knowledge production, reinforcing the inherently collective nature of sociological inquiry.

ABSTRACT. The question of urban greenery is nowadays one of the issues that come up in the urban discourse in the context of quality of life, morphological development and urban renewal projects, often being posed as challenges that the cities must face in the age of climate change. This is also the case of Polish cities and towns – as often the largest as the medium sized ones. Moreover, the recent press discourse in Poland has exposed our cities to unjustified simplifications.

At the Urban and Regional Policy Observatory, Institute of Urban and Regional Development (PL), we study the Polish cities taking into account urban greenery – its distribution, quality and role for their centres. At the same time we base our research on a theoretical, sociological framework that sees city centres as social spaces, defined by their perceived functions and needs, as a result creating a “public realm”, as Lyn H. Lofland wrote. For urban greenery not only completes public space – it also acts as a public space in its own right, offering qualities natural to the man-made public space, thus contributing to how a city centre functions.

In this paper we present a synthesis of theoretical sources for thinking about greenery as an important part of urban fabric, and methodological implications of how sociology, geography and remote sensing techniques can meet over the concept of public space. We discuss results of our original interdisciplinary studies and show perspectives for further disputes on the problem of urban greenery.

ABSTRACT. While Gen Z is often described as a snowflake o strawberry generation – emotionally fragile, anxious and unfit to face difficulties and disappointments – it is also very sensitive about environmental and social issues and often capable to capture the attention of politics, media and public opinion. From a sociological perspective, these tendencies seem to point at a general hypersensitivity, that is, an extremely high aptitude to react to what happen around, foremost formulating affective and also normative expectations and claims, leaving the cognitive approach on the background. In this sense, the world-society’s uncertainty and contingency – especially related to the future, increasingly conceived as threatening – generates different forms of psychological and affective-emotional distress (depression, anxiety, self-cutting, and so on), widely spread in the West. This research analyses the post-pandemic personal experience of the young university students in Rome, their expectations and claims, through their own self-narratives, adapting the traditional semi-structured interview technique with an experimental visual method which situates interviewees in a comfortable and “safe” environment where they could tell about their experience, biography and life without feeling judged and influenced by the interviewers. The hypothesis is that precisely the affective dimension of individuality could more clearly emerge through this method, highlighting the adaptive reactions to contingency and uncertainty of society.

ABSTRACT. How do unprecedented climate extreme events shape organizational (issue) fields and influence processes underlying attitudes toward climate change mitigation or adaptation? Answering questions about the impact of rare, extreme events poses significant challenges in the social sciences. As data capturing intricate social dynamics is often collected only post-event, issues of limited analyses and potential misattribution arise. However, recent advances in climate predictions may allow for identifying high- and low-risk regions 1–10 years into the future, enabling the observation of dynamics pre- and post-event, offering a more robust methodology.

We utilize decadal extreme hot summer predictions to orchestrate a medium-term digital field observation of urban governance, positioning it as a natural quasi-experiment. Our approach transcends outsourcing climate predictions by engaging in deep interdisciplinary collaboration to assess systemic risks, appreciate social vulnerabilities and organizational field’s institutional buffering with a novel objective: designing a sociological study that allows us to gauge not just the short-term impacts of external shocks but also the changes in network and discourse dynamics.

This requires understanding the goals and limitations of each discipline; the specific scientific principles underlying the climate statistics (e.g. the skill of predictions in vulnerable regions) and which extreme climate events could tangibly impact the social system and are observable by human institutions, redefining what hazards climate predictions should emphasize. Our study underscores the potential of intensive interdisciplinary collaboration, beyond mere synthesis. It involves exchanging and integrating statistical methodologies across disciplines, from spatiotemporal extreme event statistics to social network and semantic text analysis, while bridging epistemological gaps between physical and social sciences. While our methodology focuses on combining climate extreme predictions and digital field observations, leveraging natural science predictions in the design of future studies could benefit any sociological research that aims to understand social dynamics within a changing natural environment.

ABSTRACT. InterEd -Interdisciplinary Approaches for Innovative Education- is a two-year (2024-2025) European project funded by the Erasmus+ program, aimed at transforming teaching in secondary schools by integrating interdisciplinarity and Phenomenon-Based Learning (PhenoBL). More specifically, the main goal is to develop a teaching method that unites different disciplines, providing students with an educational experience that helps them understand and tackle contemporary challenges in their complexity. The project will develop resources like a Compendium on Interdisciplinarity, a Virtual Learning Lab (VLL) focusing on values like sustainability and inclusion, and Interdisciplinary Pedagogical Micro-Units (IPUs). To achieve this, InterEd is using a multimethod and a multidisciplinary approach: desk research, case studies, roundtables, webinars, focus groups, and experiential labs. Specifically: desk research, case studies around 4 countries (Finland, Italy, Turkey, Norway and Denmark) and roundtable were used to produce the Compendium; roundtables with academics and webinars in 3 countries (Italy, Greece, Cyprus) with both secondary teachers and academics were used to collect feedback on needs and perceptions in 3 countries (Italy, Greece, Cyprus) education systems; prior field research and a specific desk research was used to produce VLL. Next step will be the test of VLL on 36 secondary teachers and feedback collection thanks to 4 focus groups and then a pilot testing of IPUs involving 75 students and 24 teachers in 3 countries (Italy, Greece, Cyprus).

ABSTRACT. The study aims to describe the social-emotional competencies of the university student population in Italy and to examine the impact of individual and relational variables on these competencies. The research employed a mixed-methods approach, combining quantitative and qualitative analyses. Data were collected through an online questionnaire completed by a sample of 1,974 university students. The survey identified factors predictive of «self-efficacy», «responsibility» and «sociability» skills. Open-ended responses were analyzed using a Grounded Theory approach. The results show that social support, trust in others and life satisfaction positively influence social-emotional skills. However, the pandemic has weakened social networks, reducing the quality of relationships and face-to-face interactions.

ABSTRACT. Sports studies have evolved from a predominantly quantitative approach to a more inclusive research framework that integrates qualitative and mixed methods (Gratton & Jones, 2010; Diana, Catone & Taddei, 2024). This methodological shift has been essential in advancing the study of inclusive sports, capturing the diverse experiences of individuals with disabilities, migrants, those facing addictions, mental health challenges, and economic inequalities. This contribution explores the evolution of methodologies in the study of inclusive sports, emphasizing the importance of integrating and combining innovative research techniques. The analysis is based on three key elements: 1.A research study on Baskin, an inclusive form of basketball experiencing steady growth (Taddei & Bianchi, 2023). The study was conducted using a concurrent transformative mixed-methods design (Creswell, 2003), a theoretically driven approach aimed at initiating social change and providing support to the local community (Castro et al., 2010). 2.A literature review of recent studies utilizing participatory (De Cataldo & Russo, 2022) and creative research methods (Giorgi, Pizzolati, & Vachelli, 2021) in the field of inclusive sports. 3.The increasing digitalization of various aspects of sports and physical activity, which presents new opportunities for leveraging digital data and Artificial Intelligence to enhance methodological innovation and optimize the integration of social science research techniques. This study aims to identify the challenges and opportunities associated with ongoing methodological innovation in sociology and sports studies. By embracing participatory, creative, and digital approaches, researchers can develop more inclusive, effective, and impactful methodologies that advance both academic knowledge and real-world social change in the field of sports.

ABSTRACT. The media representation of Paralympic athletes is often marked by polarized narratives that swing between the glorification of disability and its denial. Some researchers (Silva & Howe, 2012; Purdue & Howe, 2012) have highlighted how the media contributes to the spread of stereotypes that shape the social perception of para-athletes. These athletes are often portrayed either as heroes with extraordinary abilities thanks to their prostheses or as athletes whose disabilities are minimized. Our study aims to explore this phenomenon from a new perspective, placing the focus on the Paralympic athletes themselves’ view. We adopted a methodological approach based on the combination of heterogeneous data and sources. On the one hand, public interviews given by athletes to the Paralympic Committee (published on YouTube) and to the newspaper Ability Channel (available on Spotify) offer an initial glimpse of their public image. On the other hand, we analyzed the digital content produced and shared by the athletes themselves on their social accounts (e.g., posts, stories, comments). The comparison between different types of data (unobtrusive vs obtrusive data [Veltri, 2019]) allows us to gain a deeper understanding of self-representation dynamics and to reflect on the opportunities and challenges related to the use of various kinds of digital data. Through this analysis, our study highlights the importance of a methodological approach that integrates multiple digital sources, offering a broader and more nuanced view of the phenomenon.

ABSTRACT. The Rome Marathon, now in its 30th edition, has undergone a very significant evolutionary process, so much so that, sociologically, it can be considered a “total social fact”: based on Mauss's theory, it involves a complex system of symbolic universes and social actors, and is much more than a sporting competition. In fact, the organizers interface with various institutional entities to establish the details of the event, the policies related to security, the adequate information and media coverage, the management of traffic and other general lines of conduct, valid and binding for the entire duration of the event. In addition to these institutional actors, there are numerous and diverse subjects belonging to the Third Sector (non-profit associations, foundations and groups of volunteer citizens) appointed to extend the public and social utility function of the event. Finally, turning to the targets of the initiative, there are athletes and spectators; tourists attracted by the event or ordinary citizens, of every generation, representatives of the local community, who participate in the event in the many ways provided (conferences and informative events on sport and well-being, group training sessions, non-competitive amateur races, music and entertainment, “themed” social occasions, etc.). To bring out the polyvalence of such a total social fact, a complex methodological system was developed, based on a mixed-methods approach, capable of enhancing forms of observation and qualitative-quantitative empirical analysis. The research design - which we intend to discuss here - aimed at highlighting and creating a dialogue among multiple aspects of a single and complex social macro-phenomenon, involved the synergistic combination of numerous techniques: from in-depth interviews with privileged witnesses and ordinary citizens of the local area, to survey research; from secondary data analysis to content analysis.

ABSTRACT. The methods used to study physical activities and body have always been divided according to the discipline conducting the investigation. In experimental sciences (biomechanics, physiology), these phenomena are analyzed using quantitative experimental setups. In social sciences, the study of physical activities or body primarily relies on traditional methods such as interviews, observations, or questionnaires (Mohr and al.2020). Research topics rarely integrate contributions from both types of disciplines.

This presentation is based on an experimental methodology used as part of a PhD project examining how the social world determines the way we walk. Its uniqueness lies in the integration of both sociology and biomechanics. Indeed, based on Marcel Mauss's conceptual framework on body techniques (Mauss, 1936) and Bourdieu's theory on embodied class differences (Bourdieu, 2000), a motion capture system was employed to quantify social class differences in walking. The objective was to integrate reflexivity and the conceptual framework of sociology with investigative methods from experimental disciplines.

The non-probability sample consists of two groups of thirty men, aged between 18 and 25, with contrasting social characteristics (in terms of capital-volume), walked 20 50-meter loops in a gymnasium. The first group was made up of students from major French universities ("Grandes écoles"), while the second group was made up of workers (skilled and unskilled) in the blue-collar sector. A motion capture of their gait was conducted, using cameras and markers placed on their bodies. Quantitative data were thus generated on the gait of each individual.

In addition to explaining the interdisciplinary framework of this study, the presentation will showcase the main statistical results. The analysis of effect sizes and descriptive statistics highlights class differences in walking styles. These results are limited because they are not inferential. Nevertheless, this study offers interesting perspectives for integrating disciplines and methods in the study of the body.

ABSTRACT. Starting from a historical discussion of the practice of dance ethnography, this article aims to reflect on actual potentiality of the interpretative paradigm and the ethnography in ethnic dances studies, both inside specific local communities as well in specific and contextualized experimental variations of our contemporaneity as stages, ateliers and performances. The main objective is to present traditional and innovative research tools to deepen the study of values and motivations in the field of dance. Moreover, on the basis of the analyzed researches, I will try to focus on the different ways through which it is possible to reveal which are the actual needs/desires for the dance community that is the object of a study through the elaboration of a list of main objectives that can be achieved by social researches on dance. Ethnography is a tool with great promise in the field of dance: it is useful to access to the differents interpretations that practitioners give to dance, linked to the different cultural and social backgrounds, and to invest the importance of dance in their ordinary life. Exploring many researches I will focus the attention on the use of notes, photos and videos during the participant observation, on narrative interviews and on the latest projecting tests and visual techniques, trying to highlight their potentialities to show how dances/movements are categorized in a certain context and, meanwhile, highlighting the possible risks which their use, due to lack of standardization, involves.

Geertz C.,(1973),“The Interpretation of Cultures.” New York: Basic Books, Inc.

Veutro M.,(2023),“Esplorare i valori. Narrazione e immaginazione come strumenti di ricerca sociale.” Libreriauniversitaria, Limena

Frosch J.,D.,(1999),“Dance Ethnography. Tracing the Weave of Dance in the Fabric of Culture.” University of Pittsburgh Press, Pittsburgh.

Hall, G.(1976]“Workshop as a Ballerina: An Exercise in Professional Socialization, in «Urban Life and Culture», 6, pp. 193-220.

ABSTRACT. Evaluation makes extensive use of methods and techniques developed in social research (Bezzi, 2001). However, unlike traditional research, its objective extends beyond understanding social phenomena to reconstructing processes and assessing outcomes directly linked to the evaluand (Stame, 1998). Moreover, evaluation data should not only generate knowledge but also inform decision-making and drive improvements within the contexts (Montalbetti, 2024). When employing methodologies originating outside the evaluation domain, it is essential to critically examine and adapt them to align with evaluative logic and the specificities of the context under investigation. Against this backdrop, this study presents an ongoing evaluation in which Social Network Analysis (Chiesi, 1999; Salvini, 2007) has been employed as an evaluative method (Durland & Fredericks, 2005) to assess the contribution of the “Vicini di Scuola” program in strengthening partnership networks. This nationwide initiative, comprising 23 projects founded by social enterprise “Con I Bambini”, aims to reduce school segregation through a range of strategies, with inter-institutional collaboration playing a central role. Given the significance of network-based mechanisms for the program’s success, SNA offers a valuable framework for mapping and analyzing partnership structures. To collect data a structured questionnaire was developed and administered to all project partnership members. The instrument focus on relational dynamics across four key dimensions: (1) instrumental processes, (2) innovation, (3) network development, and (4) network governance. The questionnaire was administered at the beginning of the projects and will be administered again at the end. This pre-post design enables an assessment of the program’s effectiveness in fostering territorial networks and enhancing collaborative practices.

ABSTRACT. This research aims to map and analyze the network of third-sector organizations (TSOs) engaged in social and environmental resilience initiatives in Naples, particularly in the neighborhoods of Soccavo and Pianura. As part of the IX Municipality, these areas are particularly vulnerable due to exposure to environmental risks such as bradyseism, flooding, landslides, and hydrogeological hazards. According to the literature, TSOs can play a crucial role in local communities, contributing to both emergency prevention and crisis management. These organizations often have a long-standing presence in the territory, and their deep knowledge of local social vulnerabilities translates into valuable resilience resources. Their embeddedness within the community enables them to act as key facilitators in disaster risk reduction (DRR) strategies, providing targeted formal and informal interventions that address both immediate crises and long-term adaptive capacities. The study follows a mixed-method approach, integrating indirect data collection (social media, websites, and literature), urban explorations, and semi-structured interviews with key stakeholders, primarily third-sector actors such as social workers, socio-healthcare operators, leaders of NGOs, volunteer associations, and social promotion organizations. Through social network analysis (SNA) inter-organizational relationships are visually represented, distinguishing between mutual and non-mutual collaborations while identifying central actors that function as network hubs. This approach provides deeper insights into resource exchange, knowledge transfer, and coordination mechanisms among TSOs. By applying relational evaluation techniques, the study also examines how inter-organizational ties influence the implementation, success, and sustainability of local interventions, particularly in natural risk situations and emergency management. Specifically, it analyzes whether and how these collaborative networks can be effectively positioned within the participatory framework of Disaster Risk Management (DRM). The findings contribute to both methodological advancements in SNA for evaluation studies and policy recommendations for more inclusive and sustainable territorial planning.

ABSTRACT. The escalating challenges confronting contemporary welfare systems have catalyzed a paradigm shift in addressing emerging social needs, fostering decentralized models prioritizing community empowerment and network activation. In this context, Social Network Analysis (SNA) has emerged as a valuable evaluation framework, as understanding relational dynamics is essential for assessing the impact of social interventions. Networks are no longer merely operational mechanisms but have become critical dimensions of impact assessment. Our research examines SNA's methodological contribution to evaluating social initiatives that cultivate collaborative networks. Complex social interventions inevitably operate through internal and external relational structures that profoundly shape implementation outcomes. The research presents an impact evaluation of a project against educational poverty in the Ragusa province (Sicily, Italy). SNA was employed to investigate the project's relational ecosystem and to assess the strengthening of the "educating community." Data collection utilized Computer-Assisted Mobile Interviewing (CAMI) at two critical junctures: mid-implementation and project conclusion. Comparative structural analysis revealed significant transformations in network expansion patterns and collaboration intensity. Integrating SNA into impact evaluation frameworks yields crucial insights for assessing intervention effectiveness and optimizing organizational structures. This approach ultimately enhances community-based social initiatives' sustainability and transformative potential by illuminating the otherwise invisible relational infrastructure underpinning social change

ABSTRACT. The evaluation of local development programmes is useful to know if what is being done, for a certain purpose, is being well done, and represents an opportunity for change for territories insofar as it allows one to know the requirements and needs peculiar to local contexts. In this sense, evaluation can be seen as a tool for capacity-building through listening to an ever-wider group of stakeholders (Casavola, Tagle, 2004). The adoption of a positive perspective (Lo Presti, 2017) is particularly suitable in the context of local development in marginal areas, as it places local actors at the centre of discovering what works and what doesn’t, fostering double-loop learning (Stame, 1998, 2016). Evaluating the social impact of local development programmes allows for observing whether, within the area of intervention, change in terms of cohesion and social infrastructures have occurred (Lo Presti, Celardi, Dentale, 2018), as well as the strengthening of relational networks. It is within this context that the objectives of the Local Development project in the municipality of Castelbuono (PA), promoted by Fondazione Con il Sud, are established. The survey involved an ex post evaluation of the project's activities, aiming to identify—independently of FCS's project action—positive changes generated for the beneficiaries and social actors in the reference context, with an openness to the unexpected. Specifically, in order to evaluate the impact of social infrastructure interventions among Third Sector Organisations, the application of Social Network Analysis (SNA) was used to gather information on the construction of relational networks and the strengthening of collaborations. To obtain a mapping of the networks, semi-structured interviews were conducted with the representatives of the local entities, organisations and associations. The qualitative study represents an interesting research result with respect to the form and intensity of the collaborations activated by local stakeholders.

ABSTRACT. In the field of healthcare, the tendency to seek organizational models based on the integration of all social and healthcare services emerges, as demonstrated by the WHO guidelines. In the Italian healthcare system, this has led to the creation of local integration systems that involve the definition of protocols and formal relationships between centres that provide social and healthcare services. Catastrophic events, such as earthquakes or floods, cause rapid and unexpected changes that undermine the planned structure of the interorganizational structure. Existing network configurations must quickly adapt to the new situation. Our work presents the results of a study involving ASUR (Azienda Sanitaria Unica Regionale) Marche in the province of Ascoli Piceno, which was hit by the 2016 earthquake, and the University of Urbino Carlo Bo, aimed at studying the evolution of the structure of the interorganisational network linking the centres involved in providing social welfare services in the field of mental health, as a consequence of the seismic event. The analysis was carried out using Social Network Analysis based on data from both databases and semi-structured interviews. In addition, in-depth interviews were conducted to investigate the meaning and context of social relationships within the network. Some indicators of network integration, already discussed in the literature, were used for the analysis. The results show that in emergency situations the network adapts and becomes denser. The evolution of the network depends both on how these external pressures are received by individual actors, and on contingent situations, such as geographical location and available resources. From the analysis of the data, it was also possible to identify the critical issues that may hinder the integration of social and health services; these include the difficulty of interacting with very different organisational cultures, territorial isolation and staff precariousness.

ABSTRACT. The study of online discourse about targeted communities has traditionally focused on hate speech, often overlooking the role of auto-narratives and self-definition by affected groups. While much research has examined the impact of hateful discourse, less attention has been given to how communities define themselves, articulate their identities, and respond to external narratives. Shifting the focus to these processes is essential for understanding digital discourse and the role of marginalized groups in shaping their representation. Auto-narratives and self-definition not only affirm cultural identity but also generate counter-rhetoric that challenges hate speech and promotes inclusivity. Anthropology has long explored how marginalized communities construct their identities, revealing the practices, symbols, and narratives they use to assert themselves in the face of systemic exclusion, providing the tools to decode the cultural frameworks and symbolic systems that shape identity formation. Ethnographic research deciphers the symbolic language and cultural codes that structure counter-narratives, highlighting the strategies that challenge racism and stereotyping. In digital spaces, these narratives emerge on social media pages run by activists, community leaders, and support networks, where individuals share testimonies, cultural expressions, and collective discourse to contest discrimination. These platforms serve as spaces of self-representation, constructing a rhetoric that challenges stereotypes and reclaims identity. Defining recurring themes, symbols, and rhetorical strategies offers critical insight into how marginalized groups navigate and reshape online narratives. This work employs ethnographic methodologies, critical discourse analysis, and textual data analysis to investigate how Roma influencers and support networks negotiate their identities in digital environments. By characterizing recurring themes and latent symbols, it examines how digital communities use shared cultural codes to construct self-narratives developing counter-discourses that challenge hate speech and affirm cultural identity.

ABSTRACT. The representation of migration in the media plays a crucial role in shaping social reality and influences public perceptions, attitudes, and policies. Social media in particular provide a space in which dominant narratives about migrants might be constructed, contested and reinforced. Previous studies have shown that traditional media coverage tends to associate migration with insecurity, threat and xenophobia. At the same time, digital platforms can both reinforce these frames and provide opportunities for participation and self-expression for migrants themselves. In this paper, we present the results of a preliminary analysis of migration-related representations in the social media accounts of selected Italian newspapers, focusing on three key events: the Cutro shipwreck, the agreement on detention centers in Albania, and the Open Arms case. The study combines quantitative and qualitative methods, including sentiment analysis, to identify dominant narratives and assess the role of migrant voices in shaping public discourse. The findings contribute to a broader reflection on the impact of digital media on integration processes and building a sense of belonging in host societies.

ABSTRACT. The present contribution investigates network dynamics underlying the dissemination of narratives and hate speech on social platforms, employing an integrated methodological approach through Network Analysis and Text Mining. This strategy of analysis can uncover intricate topological network patterns in the propagation mechanisms of narratives and racism by exploring the presence of connections among users of social media and the contents emerging in the texts shared online. Specifically, the study motivated from the fact that among minority groups, Jews have been the cyclical target of physical attacks and hate speeches. Institutions and research centres have reported a recent significant increase in online hate speeches against Jews. Noticeably, since October 7th, 2023, the terrorist attack by Hamas, and the subsequent Israeli military response and the bombing of the Gaza strip, the tendency to equate the Israeli government with the Jews and to manifest hostility against the Jews is a new kind of online antisemitism. The proposed approach is applied to detect and examine the spread of hate speech on data gathered from X (formerly Twitter), focusing on “The International Holocaust Remembrance Day”, celebrated every year on January 27. This recurrence generates online debates related to the Shoah and other historical episodes of violence, such as Israel-Hamas conflict. Often, these debates hide a veiled antisemitism, with hate speech, misinformation and extremist language, also with nuanced hate (e.g., sarcasm). By analyzing user interactions -such as retweets, mentions, and replies- we discover the presence of key nodes, influential users, and high-risk areas where such harmful content tends to circulate. Text mining techniques are then applied to construct labeled textual networks, offering novel perspectives on graph patterns, while community detection methods highlight the complex properties of these data structures.

ABSTRACT. The definition of “on-line hate speech” covers forms of expression propagating, inciting, promoting or justifying hatred based on intolerance, including that expressed in the form of discrimination and hostility against minorities. More directly, hate speech can be used in cases of cyber-harassment, to deliberately, repeatedly and aggressively harm others, in order to psychologically weaken the individual who is the victim. Besides, the concept of hatred includes other sub-concepts such as Homophobia, Racism, Chauvinism, Terrorism, Nationalism, Tolerance / Intolerance, and so on. To contrast online hatred, EC has allocated a relevant amount of H2020 funds for the completion of specific research projects. The goal is the construction of computer tools that can locate, evaluate and eventually block on-line hate speech. Today, the automatic tackling of online hatred is a daily-performed operation for Social Forums like Facebook, Twitter and Instagram. However, the algorithms such Social Forums use probabilistic Large Language Models not being able to contextualize syntactically and semantically the words used inside posts. This shortcoming may produce inaccurate results, which as for ethics can have rather serious consequences. On the contrary, we want here to demonstrate how to avoid this impasse using Linguistic-Linked Open Data (LLLOD) integrated with formalized morphosyntactic rules, such as those of negation grammar. To achieve this task, we will build detailed NooJ Italian Electronic Dictionaries, tagging entries in order to produce specific semantic expansion and “Sentiment Analysis”. This will allow us to measure and weight hate speech, assigning them values ranking from -5 (absolutely negative) to +5 (absolutely positive). NooJ will ensure these results allowing the labelling of dictionary entries using tags referring to their semantic and syntactic functions. Besides, NooJ grammars allows word contextualization, i.e., syntax formalization useful to connect the different forms of sentence with their "semantic content".

ABSTRACT. In contemporary digital society, consumer cultures and practices have been re-mediated and reconfigured by the complex sociotechnical systems of digital platforms. These platforms employ AI models and algorithms that learn from users’ consumption patterns to recommend, filter, and rank content dynamically (Airoldi, 2021). Consequently, algorithmic literacy (AL) has become increasingly important, encompassing the skills needed to understand the algorithms underlying online platforms (Zarouali et al., 2021) and to manage the default content curation settings (Bucher, 2017). The Algofeed Project, which investigates the socio-cultural effects of platform-based feedback loops (Punziano et al., 2024), has produced empirical findings on general and platform-specific digital skills, usage patterns—particularly regarding YouTube and TikTok—and cultural consumption in the Italian population. Adopting a user-centric definition of AL based on two levels of digital literacy (Frau-Meigs, 2024), the Algofeed survey examined how users present themselves online and the information they share when creating accounts and profiles. The results reveal Italian users’ browsing habits, content creation and visualization practices, their ability to discern between content produced by individuals and AI bots, and their proficiency in identifying threatening or phishing content. By integrating these survey findings with key literature (Bulger & Davison, 2018; EDMO, 2024), this contribution offers recommendations and guidelines for best practices in AL. It highlights actionable steps to enhance AL across both affective and behavioral dimensions (Oeldorf-Hirsch & Neubaum, 2025) among diverse segments of the Italian population. Ultimately, this work underscores the need for a critical, user-centered approach to digital literacy that not only raises awareness of algorithmic processes but also empowers users to navigate and regulate the digital environment effectively.

ABSTRACT. We demonstrate the concept of meta-identity to describe the synthesised, indexed, and categorised representation of individuals based on their interactions, content production, and platform-mediated behaviours. Unlike self-constructed or socially negotiated identities, meta-identity is primarily shaped by opaque algorithmic logic that prioritises engagement, visibility, and marketable user profiles.

While identity has traditionally been understood through social interactions and institutional structures, as theorized by Goffman’s dramaturgical approach, Castells’ network society, Stuart Hall’s cultural identity and other researchers in the sociological field, the digital landscape reconfigures these frameworks by introducing algorithmic mediation as an additional structuring force, leaving users and content creators with minimal control over their own digital identity.

This paper examines the influence of algorithmic decision-making on identity formation and perception by analyzing the collective work of more than 400 content creators who produced approximately 100 amateur films in digital environments. The study highlights significant discrepancies in identity attribution by comparing how these works are categorized by Artificial Intelligence models—such as those used by platforms like YouTube—against the self-perception of their creators and audience interpretations. The categorisations widely used by social media platforms may reinforce stereotypes, restrict diversity, limit user agency in shaping their identities, and induce content of a political and ideological nature for the platforms users and communities.

This study is part of a broader research project, active since 2020, exploring how meta-identity shapes social and personal identities, often with minimal individual control. The parameters used by Big Tech companies to determine algorithmic content suggestions and interactions lack transparency and remain largely incomprehensible to users. These findings highlight the need for broader public debate, greater transparency, and regulatory measures to ensure users have more control over how their data is classified and utilised.

ABSTRACT. The pervasiveness of algorithmic systems, particularly boosted by advancements in Artificial Intelligence (AI) and it Generative models, is reshaping journalistic practices and news value chain. However, journalists’ ability to critically engage with these technologies remains underexplored. Building on multidimensional models of algorithmic literacy (Dogruel et al., 2021, Swart, 2021) and AI literacy frameworks (Deuze & Beckett, 2022; Ng et al., 2021) this study investigates how Portuguese journalists perceive and interact with algorithmic systems, addressing a critical gap in current research. Employing a mixed-methods design, the study integrates an online survey of 219 journalists with three focus groups to capture both quantitative and qualitative aspects of the cognitive, affective and behavioural dimensions of the Portuguese journalist’s algorithmic literacy. The results reveal a complex and multifaceted panorama. While many journalists demonstrate an overall awareness of algorithms, they lack a deeper knowledge, with confusions between AI and algorithms operations. The affective dimension highlights a tension between the acceptance of digital tools as indispensable to remain competitive and concerns with issues like filter bubbles in social media and transparency in GenAI tools. Behaviorally, we identify that most journalists declare moderate skills in using social media, and lower skills in the use of Gen-AI tools. The results also identify a lack of structured training and newsroom support for adopting new tools, particularly Gen-AI. Based on the results we propose a framework for targeted professional development, outlining four key areas for intervention: (1) Foundational Knowledge, (2) Algorithmic Awareness, (3) Technical Proficiency, and (4) Ethical Standards. The study concludes that strengthening algorithmic literacy is vital for enabling journalists to navigate and critically engage with increasingly algorithm-driven media ecosystems.

ABSTRACT. As digital technologies and algorithms shape contemporary cultural consumption, higher arts education (AFAM institutions - it. Conservatori) must address students’ evolving social and artistic needs. This original study investigates algorithm awareness and literacy among 205 conservatory students, examining how emerging technologies influence their artistic engagement, decision-making, and perceptions of digital innovation. Most of these young and experienced artists specialize in classical opera, a field experiencing declining audience engagement and evolving industry demands. Yet, rather than being passive recipients of digital change, these "classic artists" have the potential to become key promoters of digital and social innovation in the arts. As AI-driven tools, algorithmic curation, and digital platforms reshape how cultural content is produced and consumed, classical musicians must navigate and redefine their artistic identities in an era of algorithm-mediated visibility and engagement. This study engages an uncommon team of social scientists and high arts researchers and explores artists' input on the integration of AI technologies, digital platforms, and interdisciplinary artistic approaches into new performance and educational models. Using a mixed-methods approach, the research identifies students' social and professional needs, emphasizing how they can leverage algorithmic awareness to reimagine classical opera for contemporary audiences. Findings highlight the need for educational strategies that foster algorithmic literacy, equipping students with critical skills to actively shape their field rather than merely adapt to digital shifts. The study underscores scenario-based and participatory methodologies as effective tools for cultivating awareness of algorithm-driven cultural production. This research aligns with the panel’s focus on methodological innovations in algorithm awareness, showcasing how human-algorithm interactions influence artistic identity, professional aspirations, and the future of cultural participation. By embracing digital tools and AI-driven approaches, opera students can play a leading role in bridging tradition and technological innovation, ensuring the continued evolution of their art form in a rapidly changing cultural landscape.

ABSTRACT. This article explores algorithmic awareness in the context of automatically generated memories, focusing on family practices and users with varying levels of digital literacy. With an overwhelming amount of past records, algorithms help curate personal archives by selecting moments to be remembered. Algorithmically curated memories, such as Google Photos' "Memories" (Lee, 2020) or Facebook’s “On This Day,” foster engagement with platforms and facilitate social interaction. They also play a role in identity construction, as the selection of memories contributes to narrative identity (Ricoeur, 1990). However, these technologies can also be invasive, making it crucial for users to be aware of the role of algorithms. In recent years, several studies have examined algorithmic awareness (Hamilton et al., 2014; Hargittai et al., 2020) across various dimensions (Felaco, 2022). Algorithms play a prominent role not only in public life but also in shaping intimate aspects such as romantic relationships (Felaco & Acampa, 2025) and the sense of identity (Cheney-Lippold, 2011). However, empirical studies analyzing users' awareness of algorithmic memories remain scarce. Apart from extreme cases, such as the right to be forgotten (Esposito, 2017), opportunities for algorithmic literacy on this topic through mass media are limited. Instead, interactions with other users provide the most significant opportunities for developing awareness of algorithms' influence on memory construction.This study presents findings from an exploratory analysis conducted through semi-structured interviews with family groups, addressing both memory practices and digital literacy. Group interviews within families are particularly relevant for two reasons. First, digital memories are often shared within families, both in physical and digital settings. Second, generational and digital literacy differences within the same family allow for an examination of how these factors influence algorithmic awareness and how informal, "bottom-up" forms of algorithmic literacy emerge through the transmission of digital skills among family members.

ABSTRACT. This research investigates social worker’s discretion and its learning process to understand whether and to what extent the anti-oppressive practices implemented by professionals can be passed on to trainees by training them in their role of advocacy and anti-discrimination. Anti-oppressive approach is theorised as a practice that rebalances the asymmetry of power (Freire, 2022), which may unfairly affect citizens or minorities in situations of disadvantage and vulnerability. Such asymmetry can be found in the relationship between social worker and user, manifesting itself in the form of excessive discretion from the professional. Discretion, as a practice of subjective technical judgment, is recognised as a legitimate tool for social workers. However, when discretion is exercised in an arbitrary manner, it can potentially degenerate into a means of domination and oppression, given the positional and resource advantages held by the social worker (Dominelli, 2002). To investigate whether the anti-oppressive approach and the use of discretion can be learned and fostered during the academic course, especially as part of the curricular internship, provided by Social Service courses, we chose to use a qualitative methodology of data collection, involving professionals from Italy: discursive interviews were conducted with 10 senior social workers, all of considerable experience as tutors of curricular traineeships. In addition, 10 new social workers who had recently completed their training and entered the profession were included in the study, as well as 10 social worker trainees. This helped explore different perspectives on the representation on the exercise of discretion and anti-oppressive practices learned and implemented. It was observed that the respondents experienced a process of introspection and reflection when formulating their responses to the questions posed by mentors and former trainees, as indicated by the use of the term "revelation" (Holstein and Gubrium, 1997).

ABSTRACT. Social work academics and practitioners are increasingly questioning the power dynamics in helping relationships. Reflections emerging from anti-oppressive social work approaches (Dominelli & Campling, 2002; Sanfelici, 2024) highlight how power imbalances and social dynamics that tend to marginalise and discriminate against people are reflected in fieldwork. Professionals themselves tend, often unconsciously, to perpetuate dynamics that feed forms of oppression such as ageism, disablism and racism (Thompson, 2016). The university's mission is to train future social workers who are aware of power dynamics and able to promote people's emancipation. By applying the main principles of the Relational Social Work Method (Folgheraiter and Raineri, 2017) to the field of social work education, it's possible to implement experiences of "relational teaching and learning" (Cabiati, 2017), based on the highest degree of reciprocity between teachers and students, the participation of experts with experience in teaching activities and the use of peer groups. This approach can develop students' reflexivity and critical thinking, helping them to move away from a deterministic approach to social problems and open up to anti-oppressive social work practices. The paper focuses on the importance of group work in social work education (Baldwin, 2000) as a means of enabling students to put anti-oppressive theoretical principles into practice, to reflect on the reasons for professional choices and to experiment with relationships with people and communities. The theoretical framework and group work methodology are described, with an emphasis on facilitation skills and the promotion of self-help dynamics. The strengths and critical issues of using a peer approach in a university context are also discussed. The proposed reflections are based on some data collected through an online survey of social work students and some extracts from reports written by students at the end of their practical learning experiences about their participation in group work activities.

ABSTRACT. In contemporary society, gender violence is recognized as a social and public health problem. It is rooted in an androcentric and patriarchal vision of the social world, embedded in the social relationships of power and domination. Domestic violence has additional characteristics: it uses a cyclical temporal progression and is more difficult to report to the authorities, being perpetrated by a family member. Feminist studies have undoubtedly opened up new perspectives, both from the point of view of institutional construction and the recognition of cultural and social determinants' role in supporting and promoting specific structures. However, welfare systems continue to incorporate definitions of needs and rights, as well as models and expectations of gender relations. The paper presents the research results of a case study in the Marche region. The aim was to analyze the capacity of the territorial services to support marginalized people, among which there were women welcomed into a shelter after having reported domestic violence. By adopting a participatory and emancipatory approach rooted in anti-oppressive logic, the research gave voice to the women who turned to these services. By enhancing the knowledge rooted in the co-researchers experience, the study highlights opportunities and critical points of the territorial services in the case study analyzed. It suggests integrated and innovative strategies to accompany women in the difficult paths that follow the reporting of domestic violence. The results highlight that, in many situations, the network of territorial services is the only possible option for exiting domestic violence, becoming a precious opportunity for rebuilding a new social identity. However, the practices and support strategies of public services and the third sector seem to reproduce gender representations and stereotypes that limit women's freedom of action. They impose on them the adherence to historically structured social models and roles, turning into institutional traps.

ABSTRACT. This contribution analyzes an intervention involving the relocation of Roma and Sinti families from a “village” to public housing in Venice, framing it within the classic socio-legal theme of law implementation processes (in this case, Article 11 of Veneto Regional Law 10/96, concerning housing emergency situations). Beyond the presented case study, the contribution aims to propose some useful insights for analyzing law implementation processes, particularly in the field of social policies. This includes: 1) establishing a dialogue between the literature on law implementation processes and that concerning critical social work, especially the anti-oppressive approach in social work (Scarscelli 2022), considering the latter as one of the factors influencing the use of laws in a direction that expands the enjoyment of rights by beneficiaries; 2) adopting a diachronic perspective, which, by reconstructing the history of a specific service, allows for a better understanding of the particular culture and work practices that have been structured over time within it, and thus enables a deeper grasp of the elements influencing the implementation of laws by social workers; 3) analyzing the profiles of social workers, with particular reference to their educational, political, and professional background, but also their position within the social services system: are they internal to public institutions, and thus fall into the category of street-level bureaucrats (Lipsky 1980), or are they employed within the Third Sector? 4) considering the influence of the political opportunity structures at supra-local territorial levels (regional, national, European). By applying this analytical framework, and drawing on data from both recent and past research, the article highlights some key interpretative elements that explain why, in the case of Venice, a project with at least partially anti-oppressive characteristics emerged from the implementation of this law, unlike the desegregation project of the via Anelli “ghetto” in Padua.

ABSTRACT. This paper proposes tools to assess the impact of emergency legislation on children's rights. The objective is to assess the effects of emergency legislation on the enforcement of children's rights during the pandemic crisis. It also aims to identify strengths and weaknesses in view of the need to address possible future emergencies: what worked? What are the negative/positive effects of each proposal? A comparative analysis of the emergency legislation of Italy and Poland is proposed. These two countries were selected because both of them took into consideration the protection of children's rights, which were referred to in the emergency legislation more than in the other European states. However, each state chose different paths and priorities. At an empirical level, automatic content analysis tools of regulatory texts were used. This made it possible to analyse and describe whether and how the legislative production of the two countries affected the guarantee of children's rights. Considerations also emerged on the relative priorities, the definition of childhood and the guarantees and protections provided accordingly.

ABSTRACT. This abstract presents the methodological framework that has supported and guided my doctoral research on the configuration of the child's best interest (BIC) in criminal proceedings involving juvenile offenders. Titled “Exploring the interpretation of the Best Interests of the Child principle in Juvenile Justice in Italy and Northern Ireland”, the study adopts a reconstructive approach and mixed methods to examine how the BIC is operationalized within two distinct legal systems. The research design integrates primary data – collected through semi-structured interviews with legal, social, and psychological professionals – with secondary data drawn from institutional reports, statistics, and normative documents. The triangulation of these data, facilitated by the use of NVivo, has enabled a nuanced analysis that transcends formal legal scrutiny by revealing the symbolic, cultural, and operational dimensions underpinning the application of the BIC. Inspired by hermeneutic and phenomenological models, the reconstructive approach has allowed for the categorization, comparison, and problematization of decision-making dynamics, highlighting the underlying representations and motivations driving operational choices. Notably, significant methodological challenges emerged, especially in relation to issues concerning minors, even though the research does not involve them directly. Difficulties included limited access to field data and documentary sources in the Common Law context of Northern Ireland, as well as time constraints and complex ethical and authorization procedures. These obstacles necessitated continuous adaptations of the research design and underscored the need for flexible methodological tools to critically observe the BIC in juvenile criminal proceedings and interpret its application.

ABSTRACT. This presentation will provide an opportunity to discuss an editorial project currently underway, which aims to unravel the nexus between law and borders. In dialogue with critical border studies, which have taken borders beyond their formal legal dimension to grasp their social dimensions, this book aims to put the law back at the center of reflection. In particular, this presentation will be based on the draft introductory chapter of the book and will provide an opportunity to discuss the border as an object and heuristic terrain for a critical sociology of law, then to discuss the methods that enable it to be developed, pointing out their main contributions, limits and challenges. This work is based on a theoretical framework that is strongly interdisciplinary but firmly rooted in the critical sociology of legal phenomena, and on a rich body of empirical material, collected through qualitative methods (participant and non-participant observation, in-depth interviews) on two distinct fields (southern portion of the Franco-Italian border and northern portion of the Franco-Belgian border) over a period ranging from 2015 to 2025. The volume will then be divided into two parts. The first focuses on the law in the operation of border migration control mechanisms, gradually shifting the gaze from law in texts to law in practice, in order to observe how (in)desirable and (il)legalized mobilities are concretely sorted and governed at intra-European borders, comparing both terrains and both mobilities, those labeled as transit migration and those categorized as border work. The second section draws another thread from the relationship between law and borders and uses this specific field to re-interrogate legal mobilization and the relationship between law and social movements, holding together those in support of people categorized as transmigrants, those hostile to them and those carrying the interests of so-called frontier workers.

ABSTRACT. Over the last years, in Italy, digital platforms and social media have taken on a central role in raising public awareness and in prompting processes of destigmatization of conditions characterized by pelvic and vulvar pain. These platforms, in fact, have been used by many as spaces for information, influence, mutual support, advocacy, struggle and resistance, both individual and collective, against experiences characterized by pain and medical, institutional, and social delegitimization of women, trans*, gender-fluid and non-binary people, and, more generally, people with vulvas (Holowka, 2022; Buonaguidi, Perin, 2023). This contribution will present the research design processes and the methodology we employed to analyze and make visible the main discourses and narratives about bodies, health, and needs, created and shared by the users of these platforms, and to highlight their transformative (or not) potential. In particular, we adopted a collaborative digital duo-ethnography (Burleigh, Burm 2022), employing non-participant observation, conducted across two major social media platforms: TikTok and Instagram. The presentation will highlight how this collaborative, situated and transfeminist approach facilitated the creation of spaces for dialogue, for the exploration of critical issues, including ethical ones, for unforeseen trajectories, and for the implementation of moments of dialogical and shared self-reflection (Wiant Cummins, Brannon 2021). The situated approach of this duoethnography aims to primarily recognize the epistemic value of the embodied experiences of power and oppression of those suffering from pelvic and vulvar pain.

Buonaguidi,A., Perin,C. (2023).Resisting But Embracing Fragility: Exploring Prominent Themes Emerging From Online Feminist Activists and Advocates’ Posts Addressing Conditions Characterized by Chronic Pelvic Pain on Instagram.AG AboutGender, 12(23),140–180. Burleigh,D., Burm,S. (2022).Doing Duoethnography: Addressing Essential Methodological Questions.International Journal of Qualitative Methods,21. Holowka,E.M. (2022).Mediating Pain: Navigating Endometriosis on Social Media.Frontiers in Pain Research,3. Wiant Cummins,M., Brannon,G.E. (2021).Implicating Ourselves Through Our Research: A Duoethnography of Researcher Reflexivity.Journal of Contemporary Ethnography,51(1).

ABSTRACT. Migrants have been early adopters of digital technologies with the dual purpose of maintaining communicative connections with their countries of origin while simultaneously facilitating their search for information and integration in the host country. Faced with a broad and expanding range of applications, social networks, and messaging platforms, migrants strategically select those that, due to their functional characteristics, best support their informational needs and affective relationships. In the initial stages of the migration process, these private digital environments, such as WhatsApp, play a crucial role in forming community networks that contribute to integration and social recognition in the new place of residence. This study addresses two key issues: first, it presents the methodological approach for examining these closed digital spaces where information circulates among migrants; second, it critically discusses the questions that emerge from implementing this research method. Regarding the first aspect, this research employs a combination of data collection techniques from various disciplines, including virtual ethnography and interviews with participants in these online groups. However, ethical concerns arise regarding this methodological approach: What happens when, as a migrant, the researcher is also a member of these private groups? To what extent is it ethical to simultaneously be both the subject and the object of this research? This study revolves around this dilemma as an integral part of the research process.

ABSTRACT. The analysis of digital environments presents significant opportunities for sociological research, while posing challenges related to the specificities of the digital setting and the topics being observed. The web serves as a privileged setting for studying socially significant domains, such as assisted reproductive technology (ART), a multimodal phenomenon that develops offline but finds an essential space for discussion and sharing in online contexts (Garcia et al., 2009).

As part of an interdisciplinary and mixed-methods study on late parenthood, a netnography was conducted on three digital spaces dedicated to ART. The objective was to understand how the structural characteristics of platforms influence content production and sharing. This analysis follows the principles of Follow the natives (Latour, 2005) and Follow the medium (Rogers, 2009), considering platforms and users as equal actants in determining affordances and interactions.

The comparative analysis highlights differences in terms of content accessibility, communication exchanges, and levels of mediation. Some environments promote immediate interactions, while others support more long-lasting discussions. These differences shape users’ communicative register and platform usage, creating distinct discursive ecosystems.

The onlife concept, which rejects the separation between physical and virtual reality by recognizing their interconnection (Floridi, 2014), enriches epistemological reflection. However, both epistemological and methodological challenges arise at all stages of research. Additionally, ethical and deontological issues emerge, raising concerns about data protection, privacy, and the need for ongoing reflection on ethics. Understanding platform affordances enables a deeper analysis of the role of digital spaces in constructing discursive and relational practices, providing essential tools for a more comprehensive study of online interactions.

________________ Floridi L.(2014)The Onlife Manifesto.Being Human in a Hyperconnected Era,Berlino,Springer. Garcia A.C.,Standlee A.I.,Bechkoff J.,Cui Y.(2009)Ethnographic Approaches to the Internet and Computer-Mediated Communication,“Journal of Contemporary Ethnography”,vol.38,52–84. Latour B.(2005)Reassembling the Social: An Introduction to Actor-Network-Theory,Oxford University Press. Rogers R.(2009)Digital Methods,Cambridge,MA:MIT Press.

ABSTRACT. While early studies played down ethical concerns about online research, there has been a shift towards more formal systems governing social media research over the past decade. Institutional regulatory structures like Research Ethics Boards have increasingly scrutinised these projects, with ethics forms becoming ‘gatekeepers’ for how universities organise research culture. There has been a concurrent growth in ethical guidelines for online research from organisations like the Association of Internet Researchers. Yet, there remain doubts as to how seriously ethics is treated in research, above all in studies employing data mining techniques. This is particularly salient for Digital Activism (DA) studies, where activists might be exposed to harm through their identification in publications. In response to this issue, our paper provides a critical discussion of how ethical issues are addressed in empirical DA research. We draw on data gathered from a systematic review of journal articles published between 2009 and 2024. In the first instance, mentions of research ethics were searched in protest literature more broadly (N= 264) and then in DA articles specifically (N=59). Coding categories included how ethics were narrated (e.g., popular approaches or the mention of formal procedures) as well as what attributes characterised articles discussing research ethics, for example the platform(s) studied, method(s) of data collection and analysis, authors’ institutional affiliations and their respective disciplines. We tested specifically whether empirical DA research included ethics statements, and whether articles were more likely to address ethical issues if they drew on traditional rather than digital data sources. Results indicate that very few DA articles published during this period included ethics statements. Nevertheless, there was much evidence of non-maleficence in the corpus, including those studies using digital methods. These are often rendered opaque by the submission requirements of journals and the norms of certain disciplines.

ABSTRACT. Political polarization is becoming increasingly strong, and this is most likely related to the effects of the internet, and primarily to social media (Kubin, Sikorski 2021). Political polarization takes two forms, on the one hand, we can talk about ideological polarization (Dalton 1987), which refers to the fact that political views, opinions, beliefs, and attitudes are constantly moving further apart from each other in different political spaces. On the other hand, it is important to talk about affective polarization (Mason 2018), which means that the role of identity is also becoming increasingly important in relation to political views. Those who belong to the same political side feel increasing sympathy for each other, the role of common identity is becoming increasingly important, while they become increasingly hostile towards their political opponents, identifying them as a hostile group that challenges and attacks their identity (Kubin, Sikorski 2021). On the left, there is the “Woke” side, which draws on cultural Marxism and later critical theory, including the work of Max Horkheimer, Theodor Adorno, Herbert Marcuse, Jacques Derrida, and Michel Foucault. The new right, or altright, is increasingly intertwined with the so-called “Manosphere” or “Red pill” communities, which originally focused on a specific interpretation of the problems of today’s boys and men. In my research, I examine the formation and history of these two groups, and how members of the two groups see each other and themselves. To examine polarization, I use the method of social listening (I am examining social media posts and comments from Facebook, X, Youtube, TikTok etc.). Using this method, I examine the communication of online communities belonging to the two political sides about each other and about themselves.

ABSTRACT. The Italian manosphere, similar to those in other countries, consists of various online groups that espouse anti-feminist and misogynistic ideologies. These groups, such as Men’s Rights Activists (MRAs), Men Going Their Own Way (MGTOW), Incels, and Pickup Artists (PUAs), focus on issues related to masculinity, viewing themselves as resisting societal changes that challenge traditional gender roles. Within these communities, men are often depicted as disadvantaged or victimized by evolving social norms and feminist movements. The first analysis began with a qualitative approach, such as digital ethnography, to create a network representing the online connections between these communities, particularly on Facebook, through a network analysis of 158 national pages and 31 international pages. Subsequently, two datasets were developed: the first consisting of 1,914 textual documents collected from both Facebook pages and associated blogs and forums; the second focused on the self-representations of manosphere members, analyzing the language they use to describe themselves and fellow ideologically aligned individuals, how they promote their views, share life stories, seek advice and support from their perceived peer group. Both datasets were subjected to statistical and text mining analyses, including topic analysis through Latent Dirichlet Allocation, simple correspondence analysis, and keyness analysis, that allow for an exploration of recurring themes and keywords related to gender dynamics, masculinity, and societal opposition.

ABSTRACT. With the advancement of generative artificial intelligence across the world, several institutions continue to mainstream its use into their daily activities. One institution that has witnessed a significant revolution as a result of AI is the education sector. However, there are growing concerns that humans are now allowing AI to do nearly all the work, and this fear is predominant in developing countries where regulatory frameworks tend to be largely weak. This study examines the extent to which AI is driving the erosion of academic values, especially in university thesis writing in Bayelsa State, Nigeria. Relying on a mixed-methods approach that combines quantitative and qualitative techniques, the study made use of 128 randomly selected postgraduate students at their thesis completion stage and 12 purposively selected university staff members, including the deans of faculties, heads of departments, and research and quality assurance leads. The study was conducted in two universities, Niger Delta University and Federal University Otuoke, selected based on their active postgraduate programmes. Structured surveys and key informant interviews were used to collect data from the respondents. These were analyzed using percentages and a thematic approach for the quantitative and qualitative data, respectively. Among others, findings show that unregulated use has entrenched a significant level of dependence on AI for academic writings, especially theses by students in these universities. This has significant implications for institutional policies on AI integration in the universities in Bayelsa State and Nigeria as a whole.

ABSTRACT. This contribution aims to advance an alternative understanding of platforms’ evolution premised upon their theorization as socio-material assemblages. According to it, the current shape of digital platforms in terms of practices, policies, and infrastructure emerges from the relationships between users, companies, and algorithms and their continuous redefinition. Platforms, thus, become fields of constant negotiations between companies’ race for profit and users’ interests in performing their digital activities according to their needs.

This approach entails an original strategy of research that recognizes the fundamental role played by users and algorithms in the Web 2.0 paradigm without limiting its focus on digital companies' logic. Platforms’ economic model is based upon network effect and, thus, cannot work without users’ central activity as content creators. This confers great bargaining power to them because corporations cannot lose them and, so, must adapt their policies to their requests and concerns. At the same time, the role of algorithms cannot be reduced to mere intermediaries of companies’ will. Surely, specific aims are inscribed in their design, but, when deployed in the assemblages, they modify in unpredictable ways the social reality due to users’ often unexpected perception and adaptation to them. Therefore, adopting a concept of actor-network theory, they can be defined as mediators. Following these acknowledgments, to understand the evolution of platforms is fundamental to look at the relationships established between these three elements. In particular, as suggested by actor-network theory, the focus must be on controversies, namely on the moments where these links are contested and redefined. The study of these crucial events not only can highlight the distributed agency in the shaping of platforms but can also explain and compare the different evolutions of digital assemblages and of the practices there performed.

ABSTRACT. During the current surge in generative AI development, Reddit has played a significant role in shaping interaction between humans and algoagents. Since early text generation AI models, it has been used to select "good quality" text corpora for training: for example, the dataset used to train both GPT-2 and GPT-3 were derived from internet sources linked in Reddit posts that received enough upvotes (Radford et al. 2019, Brown et al. 2020). Moreover, Reddit posts are routinely included in training datasets. As a result, generative models such as ChatGPT have inherited bias and ideological frameworks from Reddit communities, while also acquiring a strong ability to produce Reddit-like text. In fact, Reddit communities have recently experienced a proliferation of AI-generated texts, posted by algoagents posing as humans. An interesting example is the "Am I The AssHole" subreddit r/AITAH, in which users submit stories of everyday conflicts for moral evaluation by others (see e.g. Reagle 2025); recently, ChatGPT-generated stories have become common. A natural question then arises: how do users engage with machine-generated stories, and which role do these stories play in interactions between users? Moreover, since r/AITAH is dedicated to addressing moral questions, how does the machine contribute to the collective negotiation of morality within the community? My contribution presents a quantitative-qualitative approach to tackle these questions. AI-based automated techniques are paired with human analysis to investigate a corpus of roughly 20.000 posts, spanning two years between 2023 and 2025. Key questions, both methodological and content-related, pertain to the phenomenon’s diffusion (and how to measure it), user reactions (both to AI-generated stories and to algoagents themselves), and the interactions it generates between users.

ABSTRACT. This study explores how AI models such as GPT, increasingly present in higher education, reshape not only learning practices but also fundamental definitions of academic integrity and ethics. Drawing on a triangulation of data sources — an extensive student survey (N = 792), desk research of existing AI-in-education studies, and three focus group interviews with students from different academic disciplines planned for March 2025 — we examine how AI use is embedded in diverse learning contexts at AGH University and how it contributes to redefining academic practices and ethical norms. Rather than viewing AI solely as a tool, we approach GPT as an algorithmic agent (“algo-agent”) that participates in constructing academic norms and values, influencing the boundaries between what is deemed acceptable or unethical. Our findings illustrate that AI systems create new possibilities for learning (such as personalized assistance, scaffolding for complex tasks), but simultaneously introduce new forms of academic risks and ethical dilemmas (e.g., reliance on AI-generated content without transparent acknowledgment, gaming the educational process). Crucially, AI tools challenge traditional notions of learning effort and authorship, pushing universities to reconsider what constitutes an “authentic” academic output. This emergent reality points to a reconfiguration of power, agency, and knowledge within the university, where AI is not merely supporting learning but actively shaping the epistemic and normative order. Methodologically, we reflect on what it means to study AI as a co-actor in education and how recognizing AI as an active participant compels us to rethink responsibility, agency, and the social construction of ethics in academia. We argue for theoretical models that acknowledge AI as a normative force and outline challenges for building a critical AI literacy that goes beyond technical skills, focusing instead on understanding the ethical, political, and social implications of AI’s integration into higher education.

ABSTRACT. This contribution explores the creative and methodological potential of using commercial artificial intelligence platforms — specifically GPT and DeepSeek — as innovative tools in sociological research, with a particular focus on netnographic research and social network analysis. Based on the author's doctoral research project examining online narratives related to the Russo-Ukrainian war (2022-2024), the paper proposes a methodological evolution from the traditional approach of manual content coding by expert human coders (Schreier, 2012; Faggiano, 2022) to a methodological framework based on training artificial coders.

The theoretical foundation of this project originates from previous studies on the socio-semiotic dimensions of war narratives, particularly concerning the conceptualization and operationalization of "fabulation" and "testimony" (cf. Jedlowski, 2022). Initially, these narrative dimensions were manually detected by expert researchers specifically trained to identify semiotic indicators — including "polarization", "calls to action" and "memetic potential", namely semantic marks (or connotations) related to "mythology", "surface" and "deep" imaginary (Giungato, Taddei, Affuso, 2024). Although valuable, this process is limited by subjective biases, interpretative variability, and the restricted number of potentially analyzable texts. The introduction of AI platforms offers an alternative approach that combines systematic analysis with interpretative creativity.

Thanks to a preliminary and necessary phase of specific training aimed at creating an interpretative alter-ego of the researchers, AI can even suggest novel interpretations, identify semantic connections not immediately evident, generate new analytical categories, and reveal latent narrative patterns. Epistemologically, this approach centers the debate on the symbiotic and instrumental relationship between the human researcher and AI, simultaneously highlighting significant ethical considerations such as authorship of analyses, interpretative biases, and researchers' creative responsibility. Such interactive and iterative experimentation thus transforms artificial intelligence into an active creative participant, significantly contributing to sociological knowledge construction and expanding interpretative and imaginative capacities for understanding complex digital phenomena.

ABSTRACT. In the wake of the global push for green and sustainable development, governments and social organizations are urging companies to enhance their social responsibility and proactively consider the interests of various stakeholders. Organizations are under increasing pressure to showcase their dedication to sustainability through Environmental, Social, and Governance (ESG) performance metrics (Galeone et al., 2024; Ding et al., 2024). The intersection of technological innovation and sustainability goals offers valuable opportunities to explore the impact of AI adoption on corporate ESG practices. The implementation of Fintech services provides significant potential to strengthen and advance organizational ESG initiatives. However, scholarly understanding of these relationships remains limited (Trotta et al., 2024). Our research addresses this knowledge gap by investigating Fintechs’s impact on corporate ESG performance among US listed enterprises. In particular, we consider Penalized Generalized Estimating Equations (Penalized GEEs) for high dimensional longitudinal data analysis in order to investigate: How does Fintech development in European enterprises affect their ESG performance? This study makes two key contributions to the existing literature. First, it offers strong empirical evidence on the relationship between AI development and ESG performance within the context of an emerging market. Second, our text-based AI adoption metric introduces a novel method for quantifying the extent of AI integration within organizations.

ABSTRACT. In the context of the 2030 Agenda for Sustainable Development, an action plan adopted by the United Nations in 2015 to achieve 17 Sustainable Development Goals (SDGs), it is important to understand the interconnections among these goals, which are measured using both simple and composite indicators. In particular, achieving Sustainable Development Goal 10 (Reducing Inequalities) requires a deep understanding of the interdependence among various socio-economic indicators. In literature, income, education, and health have consistently been identified as key dimensions influencing inequality dynamics. However, analyzing the large number of indicators related to these dimensions poses challenges due to their high collinearity and dimensional complexity, which may affect the robustness of findings and the effectiveness of policy interventions. This study extends previous research on poverty and inequalities in Italy to a European context, examining dependent relationships among inequality-related indicators across multiple countries. Specifically, we employ four regression models: RIDGE, Least Absolute Shrinkage and Selection Operator, ELASTIC NET and Partial Least Square. These models are widely recommended in literature to assess relationships while addressing multicollinearity issues. A crucial aspect of our approach is the evaluation of result stability, implemented through bootstrap resampling methods, which allow us to quantify the variability and reliability of our estimates. Our findings contribute to the debate on how to effectively monitor SDG 10, providing policymakers with a statistically robust framework for assessing inequalities. This study highlights the importance of using advanced statistical methods to enhance the reliability of inequality measures, ensuring that policy recommendations are based on stable and reproducible results.

ABSTRACT. This study investigates the relationship between perceived quality of care and the scientific and social impact of Italian Academic Health Science Centers (AHSCs), addressing the complexity of high-dimensional data inherent in sustainability-related research. The main objective is to assess whether enhanced scientific productivity corresponds to improved patient perception of care quality, thus offering evidence to inform strategies at the intersection of research excellence and healthcare service delivery. To this end, a comprehensive dataset was created, by combining data from diverse sources such as clinical trials, patents, competitive research funding, bibliometric indicators, and altmetric scores, reflecting both scholarly and social visibility. Perceived quality of care was operationalized through user-generated reviews and ratings from digital platforms, serving as a real-world proxy for service evaluation. The analysis adopts E2Tree, an approach specifically designed to improve the interpretability and explainability of ensemble models like Random Forests. E2Tree enables the disentangling of complex variable interactions, offering clear insights into variable importance, groupings, and nonlinear associations in a high-dimensional context. By enhancing transparency in model behavior, E2Tree supports informed decision-making and bridges the gap between predictive accuracy and achieving a deeper understanding. Results highlight which dimensions of scientific output and social dissemination are most strongly associated with positive patient perception. Beyond the methodological contribution, this research aligns with the Sustainable Development Goals (SDGs), notably Goal 3 (Good Health and Well-being) and Goal 9 (Industry, Innovation and Infrastructure). It underscores the value of explainable machine learning tools in fostering sustainable healthcare systems, where research impact and care quality are evaluated in an integrated, data-driven manner.

ABSTRACT. Between 2023 and 2024, a comprehensive study examined local community responses to global sustainability crises. The research focused on community services and community practices. The research was mainly conducted using a combination of qualitative and quantitative methods, using descriptive and classifying methods. The detailed description, systematisation and categorisation of the social phenomena (sustainable community services and practices) was carried out through literature review, focus group discussions and workshops, and guided interviews. During the focus group discussions, together with the invited Hungarian experts, the researchers developed a set of criteria suitable for the detailed description and analysis of community services, practices and working methods. Based on the experience of the focus groups, structured interview drafts were prepared. Using these measurement tools, the researchers began to collect good examples and produce descriptions of community-based practices. The researchers built a knowledge base repository of community services and practices. More than 80 case studies and 64 interviews were conducted. The research generated a large volume of textual documents. The categorisation of good practice was facilitated by coding and text analysis techniques (e.g. word clouds) and the use of quantification methods. The research used a working definition and traditional methods to create a model of the community service process. The aim is to answer: How to find the common definition using innovative AI tools in the Hungarian language, such as adapting and fine-tuning natural language processing methods to answer community developers' questions? How to find a new, summarised Hungarian definition of community-based services and good practices and create new, optimal processes (models) of community-based services? How can generative AI tools help us to perform automated content analysis of our texts and interview material?

ABSTRACT. Over the past two decades, there has been growing interest in using synthesis measures like composite indicators. A Composite Indicator is a valuable tool for consolidating data on complex, multidimensional issues, aiding in policy decisions. However, its normative nature and the tendency to use a single Composite Indicator to represent intricate phenomena have often been criticized. This paper introduces an exploratory, simultaneous approach for developing a Composite Indicator system that captures various dimensions of a phenomenon. This approach, known as the Ultrametric Composite Indicator model, reconstructs the hierarchical relationships between observed variables, which are identified through the correlation matrix, using an extended ultrametric correlation matrix. The Ultrametric Composite Indicator model is used to analyze waste management in Italian municipalities, a complex issue that provides valuable insights into municipal practices concerning waste collection and disposal. Additionally, it serves as a tool to support local councils in Italy in making well-informed policy decisions.

ABSTRACT. The paper proposes methods of sociodigital futures inquiry that can engage with both the technical understandings of black box systems and the diverse socio-political contexts within which such systems are developed. We report the entangled approaches adopted to understand a predictive analytic system for identifying vulnerable children in one English Local Authority. Since November 2023 we have been investigating this system which comprises large-scale data linkage with in-built risk modelling. Our research has employed freedom of information (FOI) requests and we reflect on how FOI can be usefully deployed (and its limitations) to generate insights and potentially intervene in sociodigital futures in the making (Van Isacker & Walters, 2024). We have also been piecing together information and insights through discussions with investigative journalists, activists and other academics, alongside community and council stakeholders who have brought different perspectives and challenges to bear concerning the futures scripted through this system as we support that inscribing a particular role into a technological artefact implies prescribing corresponding roles to human actors (Schulz-Schaeffer, 2021). We have drawn on assemblage theory (Deleuze & Guattari, 1987) and the methods of tracing and mapping to chart open systems that are contingent, unpredictable, and productive (Martin and Kamberelis, 2013) and reveal the intra-actions (Barad, 2007) between societal drivers and contexts and digital solutions. We also take on critiques that mapping automated technologies is not a benign abstract act (Sleep, 2022) and the need for a counter-mapping approach that asks critical questions about what big data is being used, how it is used, and who it affects (Redden, 2018) and that actively recognises the impacts of both bureaucratic decision-making and technological change in the adoption of the predictive system researched here.

ABSTRACT. Artificial Intelligence (AI) models are entangled with the sociodigital environments shaping contemporary knowledge production. Building on an intra-action perspective, these models are understood as co-constituting future-oriented practices. Predictive and generative systems embody “learned futures” derived from training data, algorithms, and infrastructures, reflecting the complex, dynamic processes up to, during and after their deployment. This contribution presents ongoing work on prompting for model outputs to examine how these learned futures are constructed, while testing established futures methods on AI models as nonhuman research subjects. Similar methods have historically been used with human participants, but it is argued that they are already adopted, even if not rigorously, with AI models in research, design and decision-making. Findings highlight the affordances and constraints of applying scenario thinking, forecasting techniques, and other anticipatory frameworks to machine-generated content. Differences from human-based futures research are discussed, particularly regarding the interpretive challenges of model outputs and the methodological implications of model-driven anticipation. These insights inform the development of innovative and participatory approaches for engaging with AI in collaborative endeavours and advance methodological conversations on researching “futures in the making”.

ABSTRACT. The embedding of digital data, devices and infrastructures within social life is a feature of the 21st Century. Social relations are being reshaped across many societal domains, and significant challenges to social sciences emerge.

This transformation is evident in the world of work, where platforms and artificial intelligence operate as Black Boxes (BBs). Their automatic decision-making and data management are complex to understand. The lack of transparency raises risks for workers’ fundamental rights, including pervasive surveillance, discriminatory treatment, and unjustified dismissal. Ensuring workers’ protection requires methodologies to understand how BBs operate. This question is crucial for researchers, trade unions, and labour courts.

This paper proposes a sociological approach to the Black Box Test (BBT) commonly used in the software industry to ascertain the proper functioning of the products before distribution. First, it examines the problematic presence of BBs in the workplace. Second, it deconstructs the structure of a BB, identifying four analytical layers that provide information into its functioning: user interfaces designed to enable human-machine interaction; the software installed on the user's device, which connects it to the BB’s IT system; data flow between the user's device and the IT system; the BB’s IT system, responsible for automatic decision-making. The third part illustrates a sociological approach to BBT, using interview techniques and observation of digital artifacts. This methodology emphasizes information about the functioning of BB functioning that is outside of it, such as those that are part of the user experiences, or are situated in the superficial layer. By combining this information, it becomes possible to reconstruct the functioning of BB, and verify potential or actual harm to workers’ rights.

This method could also be applied beyond the field of research, serving as a valuable tool for lawyers and judges, and being accessible through technical consultancy assignments to sociologist experts.

ABSTRACT. Sociological research boasts a long-standing tradition in exploiting newspapers as a data source for investigating social phenomena. This tradition has gained renewed momentum due to increasing digitalization processes, which have made vast quantities of digitized articles available for social research, coupled with the development of automated analysis techniques that enable efficient processing of such data. Current journalism is a proper sociodigital phenomenon: contents are growingly created to adhere to online communication requirements, they circulate crossplatform and they are available as texts. The TIPS (Technoscientific Issues in the Public Sphere) project aligns with this context, for over a decade, has conducted numerous studies leveraging the capabilities of its purpose-built web platform. Our presentation aims to showcase significant research outputs by the TIPS research group. The examined cases will illustrate how TIPS addressed methodological challenges of social research applied to digital data: by experimenting various analytical techniques, ranging from automatic classification to topic modeling, from Named Entity Recognition (NER) combined with network analysis to the latest developments in Artificial Intelligence (AI) TIPS project developed. This approach will offer the opportunity to explore advantages and limitations of research based on newspaper publications but also on its utility in analyzing socio-digital phenomena, both emerging or long-standing. Furthermore, we will discuss some epistemological and methodological implications arising from the application of the analog/digital dichotomy in social research, particularly when simplistically equated with the real/virtual distinction.

ABSTRACT. This submission proposes a dialogue between the field of Applied Linguistics (research line Languages ​​and Technologies) and the research field on sociodigital futures. We intend to present a multidimensional model based on an alternative philosophical approach to human-AI interactions, with a particular focus on large generative AI systems, aiming to contribute to the development of research, practice and policy agendas that promote critical AI literacy in Brazil. Highlighting the “foundational” aspect of this AI technology, we argue that its sociocultural, ethical and epistemic impacts must be considered, as well as the need to move away from metaphors and personifications that create a division between humans and AI as mere tools and instead adopt an “ecological” – and also sociodigital – vision in which AI is seen as a cognitive assemblage involving machines and humans. The essay draws on the ideas of Katherine Hayles and the post-phenomenology of technology (Don Ihde), analyzing how language interfaces between humans and AI agents create effects of intelligence and quasi-subjectivity. Practical applications of this model are proposed as a methodology for exploring AI literacy events.

ABSTRACT. Algorithmic memories are digital records of users' online activities (posts, photos, and metadata) organized narratively by intelligent systems. Popular services such as Google Photos, Apple Photos, and Facebook's "On This Day" feature exemplify this phenomenon. While algorithmic memories help users manage their digital traces, they also raise ethical concerns, particularly regarding privacy, identity, and the potential impact on personal memory. Understanding users' awareness of "memory algorithms" is crucial, including concerns about the future of memories mediated by AI. To examine user awareness of algorithmic memories, it is essential to consider them as sociodigital objects—culturally constructed artifacts shaped by social theories and multiple actors, which, in turn, influence practices of remembering. Algorithmic memories evolve over time, adapting to changes in technological affordances and materiality. Awareness of these dynamics is both cognitive and practical, encompassing users' perceptions as well as their strategies for preserving memory authenticity and autonomy over digital traces. This paper argues that studying users' awareness of algorithmic memories requires a pluralistic and critical methodological approach to reveal the entanglement of social and digital factors in shaping future memories. Approaches that focus solely on technological features or social practices fail to capture their interwoven nature. Methodologically, this results in oversimplifications that overlook material, intersubjective, and cultural complexities. We discuss the benefits and limitations of qualitative and digital methods, integrating insights from critical algorithm studies. Finally, we advocate for an interdisciplinary approach that accounts for both the cognitive and social aspects of memory.

ABSTRACT. Many studies in the field of higher education use distance as a simple measure of accessibility, commuting, or moving. They often define distance as the straight-line distance, while only a few studies measure distance using the actual travel distance. This approach is supposedly more sophisticated, accurate, and realistic. Our aim is to assess whether the straight-line is an adequate proxy for travel distances by car and multimodal public transportation in Germany.

We compare the straight-line and the travel distances between the former school and the current university. We also distinguish between the shortest and the best route. The linear relation between the straight-line and travel distance was analyzed using ordinary least-squares regression. To examine outliers, the difference between the actual travel distance and the predicted travel distance, which is the straight-line distance multiplied by the regression slope, was used. The straight-line distance is a good proxy when the absolute difference between the actual travel distance and the predicted travel distance is less than 5 km, or the relative difference is less than 10 %. The results are based on a representative sample of 2,903 different routes taken by German students.

In 96 % of the cases, the straight-line distance is an adequate proxy for the shortest travel distance by car. However, the straight-line is a good approximation of the best car route 80 % of the time. For the shortest and best public transportation routes, the straight-line is a reliable proxy 66 % and 60 % of the time, respectively. The largest discrepancies occur in areas with physical obstacles such as lakes, rivers, mountains or wilderness and nature conservation areas. These findings suggest that future studies should use travel distances for more realistic results, as they provide significantly greater accuracy than straight-line distances.

ABSTRACT. Different planning concepts highlight how integrating spatial and temporal dimensions in urban design can advance sustainable accessibility and well-being. Approaches like the X-minute City (XmC) emphasize locating daily services and amenities within close reach, mitigating spatiotemporal injustice and reducing car dependency. Yet, a key challenge lies in developing robust methods to analyze the spatiotemporal dimensions of these opportunities specifically for older adults living in smaller cities who can face unique mobility barriers.

This paper presents a methodological framework for understanding how older adults (65+) navigate service availability across space and different time frames. First, we apply a chronotopic mapping approach, analysing spatiotemporal open data—e.g. store opening hours and GTFS transit information—to generate mobility and opportunity sketches of daily points of interest in three case studies located in Czech Republic, Estonia, and Sweden. These study areas, differing in size, governance, and urban characteristics, offer diverse insights into the interplay of context-specific spatiotemporal factors. Second, participatory mapping sessions will enrich these sketches as older adults use mapping and GIS tools to locate anchor points and share personal mobility narratives. These narratives highlight individual routines, place-based meanings, and time constraints shaping daily mobility strategies.

By integrating quantitative analyses of transport and service datasets with qualitative insights from participants, we illustrate how barriers arise where local infrastructures, public transport, service hours, and rhythms intersect. In exploring the XmC concept—underscoring accessible local services without presupposing travel time or speed in contrast to 15mC concept—we explore whether and how mismatches between older adults’ needs and urban temporal structures compromise accessibility. Finally, by discussing the use of data from multiple case studies, including OpenStreetMap, we address challenges related to data consistency and availability. Taken together, our contribution stresses the value of inclusive data practices and participatory engagement in shaping more age-friendly planning.

ABSTRACT. This contribution reflects on the methodological challenges and opportunities emerging from the innovative use of diverse data sources in mobility studies, drawing from experiences within two recent research initiatives: the Spoke 8 - MaaS and Innovative Services of the National Centre for Sustainable Mobility (MOST) and the Spoke 1 - Urban Regeneration of the Ecosystem MUSA - Multilayered Urban Sustainability Action. Focusing specifically on the mobility patterns within Milan’s Bicocca neighbourhood, these projects integrated a variety of novel data sources – including telco and traffic data, surveys, sensors for the detection of flows, soundscape and air quality – as well as methodological approaches such as urban audits, spatial analysis, surveys, and mobile methods. The presentation introduces the case of the “Bicocca Mobility ID Card” emphasizing how these combined methodological tools offer unprecedented potential to analyse urban transformations, mobility behaviours, and the interactions between diverse social groups and the built environment. At the same time, it critically addresses significant methodological risks, notably the fragmentation of knowledge due to an excessive focus on detailed data descriptions at the expense of theoretical and systemic comprehension. Moreover, substantial integration difficulties arise from data expressed in different units of analysis, accompanied by an observed tendency towards excessive data engineering and aestheticization. Further complicating this scenario is the low transparency surrounding data collection techniques and original purposes – often linked to commercial rather than scientific objectives - which raises critical concerns regarding the reproducibility and reliability of these novel spatial data. This “black box” problem underlines the necessity for greater methodological awareness and rigorous scrutiny in handling innovative data sources for mobility research.

ABSTRACT. Public transport (PT) is crucial for sustainable development and access to opportunities in urban and rural areas. However, the sector is facing a crisis in working conditions and labour supply. Swedish trade unions report deteriorating conditions, including long, stressful days, unpaid breaks, and inadequate rest spaces. Additionally, PT operators are experiencing a severe staff shortage, leading to frequent service disruptions.

The everyday work of bus drivers is characterized by a complex and rigid spatiotemporal configuration, which appears to limit their agency and well-being at work while also affecting their non-working life. Bus drivers operate a crucial part of the system of everyday mobilities and, at the same time, are also mobile subjects that move across the built environment before, during, and after work.

This paper discusses the use of mobile methods to grasp the everyday work experiences of bus drivers. The data collection involves mobile ethnography, including ride-alongs and in-depth interviews, to understand bus drivers' work practices and the organisational conditions contributing to shaping them. Twenty drivers from two Swedish regions, covering various service types, will be interviewed and observed during their shifts. Special attention will be given to the spatiotemporal aspects defined by duty schedules and PT timetables, and the power dimensions related to gender, racial, and class relations surrounding them.

Our contribution addresses how to operationalize an intersectional and spatiotemporal framework in mobile ethnographic fieldwork. It highlights methodological challenges related to exploring the relationship between spatiotemporalities and workers' gendered, racialized, and classed experiences and agency (e.g., participation, adaptation, resistance). Addressing these challenges is crucial to ensure that results from the mobile ethnography reflect the bus drivers’ experiences and provide applicable insights for improving their working conditions.

ABSTRACT. The accessibility to urban amenities and services of general interest is considered as a proxy for defining and identifying peripheral areas within cities. Despite the evolution of the concept of periphery over time, and its subsequent linkage to non-spatial factors such as socio-economic conditions, accessibility remains a pivotal aspect in the study of disadvantaged city areas. Indeed, the adequate accessibility to desired opportunities and services constitutes the basis for spatial justice and social inclusion. A plethora of methodologies and approaches for the study of accessibility have been proposed in the scientific literature. Some of these approaches consider services achievable by walking, and/or the concentration of amenities calculated with gravity models. Other studies have focused on the provision of transport infrastructures, such as metro and railway stations or bus stops, or analysed the accessibility through private motor vehicles, measuring distances based on road networks. However, only a few studies have examined the accessibility of services in relation to public transport availability. The present contribution aims to propose an analytical method to identify the peripheries of access to services through public transport systems. Specifically, the study proposes an analysis of the city of Rome, using the public transport open data in General Transit Feed Specification (GTFS) format to measure temporal distances to amenities available from other open data, such as OpenStreetMap. The analysis identifies a classification system based on the concept of peripherality to define a range of accessibility levels across different urban areas. Furthermore, the proposal aims to address several methodological concerns, including the varying accessibility levels in relation to urban rhythms and diurnal and nocturnal variations; the necessity to adjust accessibility according to diverse user profiles, groups, and urban populations; and the ranking of opportunities, thereby enabling the identification of various acceptable access thresholds.

ABSTRACT. This study investigates how media consumption patterns shape anti-establishment voting in Romania, with a particular focus on the 2025 presidential election campaign. This electoral period is marked by an unprecedented political crisis following the annulment of the 2024 presidential elections, when outsider Călin Georgescu unexpectedly won the first round with a declared campaign budget of 0 RON. His subsequent disqualification by the Central Electoral Bureau in March 2025 further deepened political tensions, fueling polarization and distrust in electoral institutions. Using two nationally representative surveys conducted by IRES, we examine how voters of two key anti-establishment parties—AUR (a right-wing populist party) and USR (a centrist anti-elite party)—engage with different media environments. Our findings highlight distinct consumption habits: 63% of AUR voters primarily rely on mainstream TV news, but 19% turn to social media (Facebook, Instagram, TikTok, YouTube) for political information, a higher proportion than PNL (17%) and PSD (17%) voters. In contrast, USR voters favor online news portals (23%) and social media (28%), with significantly lower reliance on television (34%, compared to 52% for PNL and 77% for PSD). These distinct informational pathways reinforce political silos, deepening polarization. To analyze how these fragmented media ecosystems shape political discourse, we will apply computational analysis of digital interactions during the campaign. Using network analysis (UCINET), we aim to map voter interactions and detect echo chambers and clustering effects among AUR and USR digital communities. Additionally, sentiment analysis of social media debates will be use to assess how emotions such as distrust, outrage, and mobilization narratives drive engagement. We argue that digital media consumption strengthens anti-establishment mobilization and facilitates micro-targeting strategies. By integrating survey data with computational methods, this study offers a multi-method perspective on the role of digital platforms in shaping electoral dynamics in a moment of profound political disruption.

ABSTRACT. The past decade has witnessed a notable surge in populist movements across Europe, encompassing both right-wing and left-wing parties. Their euro-skeptical narratives often challenge the legitimacy of the European Union, with right-wing populism fostering nationalist and exclusionary ideologies that undermine core democratic values. Spain reflects this growing trend, as various political entities leverage social media platforms to propagate distinctly populist messages during electoral campaigns. This paper presents an in-depth analysis as part of a comprehensive international research initiative addressing the intersection of polarization, populism and post-truth politics. In this study we investigate the manifestations of populist discourse in the lead-up to the 2024 European elections in Spain. Our conceptual framework defines populism as a strategic discourse characterized by anti-elitist rhetoric, an idealized vision of the people, and a commitment to popular sovereignty, requiring at least one of the latter two elements alongside anti-elitism for classification as populist. By analysing the official communication from parties represented in the European Parliament, we will employ combination of manual term classification and advanced graph theory techniques -including density analysis, centrality assessments, and community detection- to elucidate information flows and interaction patterns. Additionally, we will utilize Large Language Models LLMs) to identify and categorize predominant themes within populist rhetoric. This study aims to contribute to the understanding of how digital platforms shape political narratives and the implications for European unity amidst rising populist sentiments.

ABSTRACT. Political polarization represents one of the most significant challenges to democratic discourse, with direct implications for public debate and electoral outcomes. This study addresses political polarization by analysing textual content from Facebook and X (about 2634 posts), classified according to a polarization scale ranging from extreme left (-7) to extreme right (+7), including neutral (0). Employing quantitative descriptive methods and topic modelling techniques, specifically Latent Dirichlet Allocation, we explore the distribution and characteristics of political polarization within posts generated by Italian politicians and parties during the last European political elections, related to relevant socio-political issues. The analysis highlights distinct thematic clusters emerging within polarized groups, revealing the core linguistic and topical differences between posts polarized toward the left or right. Furthermore, through hermeneutic analysis, we examine whether the polarization of topics identified is associated with elements of populist communication, such as appeals to emotions, simplification of complex issues, construction of antagonistic identities ('us versus them'), and elements of post-truth, such as selective interpretation of facts, rhetorical strategies, and dissemination of partisan narratives. Our findings provide empirical insights into how polarization, populism, and post-truth phenomena intertwine and are strategically employed in political communication during significant democratic processes such as the European elections.

ABSTRACT. One of the major challenges in international sociological research groups is creating an analytical environment that simultaneously integrates common analytical dimensions and events (or phenomena) of shared interest while preserving the regional and cultural specificities of different research centers and their respective contexts for local or regional analysis. The complexity of contemporary political and media dynamics demands methodological frameworks that are both adaptable and rigorous, ensuring comparability across cases without losing local nuances. This presentation introduces the data model proposed for the 3Ps research group. It is designed to support investigations on polarization, populism, and post-truth across different levels of analysis by using mixed approaches to social and data science. The model is designed to provide researchers with structured methodologies to examine multiple digital and media discourse dimensions, facilitating comparative analysis across diverse sociopolitical landscapes. The study focuses on the integration of data analysis techniques applied to: 1. Political discourse on social media, including posts and interactions from political groups. 2. Traditional and social media content analysis, examining news framing and dissemination patterns. 3. Argumentative analysis of political speeches and publications, identifying rhetorical strategies and discursive structures. 4. Meta-analyses of academic articles and publications, consolidating existing research findings on the 3Ps phenomena. By applying this model to the cases of Portugal, Spain, and Brazil, we explore the methodological challenges, solutions, and future directions in structuring large-scale social data for political and media discourse analysis. This research contributes to the broader field of computational social science by demonstrating how structured data integration can enhance the comparability, depth, and interdisciplinary collaboration in social research while preserving theoretical and contextual integrity.

ABSTRACT. Purpose: This study will examine how political polarization manifests in the Italian debate on differentiated autonomy (2023-2024) through an analysis of discursive practices in traditional and social media. It investigates how territorial divisions are articulated in public discourse and identifies rhetorical mechanisms that intensify political polarization surrounding governance reforms. Design/methodology/approach: The research will employ a multi-platform discourse analysis combining two data streams: (1) systematic collection of articles from national and/or regional newspapers between January 2023 and December 2024, and (2) targeted sampling of Facebook and X (Twitter) posts containing relevant hashtags and keywords (#autonomiadifferenziata, #NordControSud). The corpus will be analyzed through thematic coding, rhetorical analysis, and examination of narrative frames to identify patterns of polarization across different media environments. Findings: Preliminary results indicate distinct rhetorical strategies employed by competing territorial actors, wherein identical policy proposals are framed as either essential reforms or existential threats. Traditional media reproduce institutionalized North-South divisions, whereas social media platforms exhibit more complex polarization patterns that transcend geographical boundaries, creating trans-regional discursive coalitions organized around ideological concerns rather than strictly territorial ones. Originality/value: This research offers methodological innovations for the study of political polarization in territorial disputes by focusing on discursive practices rather than voting patterns or economic indicators. It contributes to scholarship on the "3 Ps" (Polarization, Populism, Post-truth) by demonstrating how center-periphery tensions are amplified through media discourse, providing insights applicable to territorial governance disputes beyond the Italian context.

ABSTRACT. The connection between healthcare measures and democracy has been widely debated, particularly in light of the growing influence of ultraconservative rhetoric challenging vaccination policies. This study examines the impact of such discourses, focusing on far-right narratives shaping HPV vaccine hesitancy in Brazil. It explores political narratives, assessing how denialism and moral arguments surrounding sexuality undermine institutional trust and weaken immunization adherence. Adopting a qualitative approach grounded in Critical Discourse Analysis and Science Data techniques, this study examines digital disputes over the HPV vaccine on Instagram from 2018 to 2025. The analysis is based on social media posts and their comments, mapping the interactions between groups. Data collection was built using Content Library via META. The study employed a data-processing tool called Ford, designed to extract data from Content Library and previously from CrowdTangle, allowing for a structured representation of clusters based on homophilic ties between Instagram channels. To visualize narrative conflicts and the actor-network, Gephi software was used to generate both actor and word graphs. Primary findings reveal three key dimensions: 1. The portrayal of childhood as a moral battleground, where HPV vaccination is framed as a catalyst for premature sexual initiation. 2. The systematic weakening of social participation, as conservative actors disrupt health councils and community-led initiatives, thereby dismantling collective decision-making structures. 3. The strategic use of misinformation, which amplifies distrust and fear regarding vaccines, reinforcing ideological polarization. By linking public health debates to the broader crisis of institutional trust, this study highlights how polarization actively reshapes immunization policies in Brazil. Finally, from a methodological perspective, this study also enables the sharing of scripts and data mining processes for large datasets extracted from the Content Library, ensuring that researchers can conduct new experiments and make further discoveries in the field of studies involving digital methods.

ABSTRACT. In a digital era of social hypertransparency, external perception and image are now considered among the most significant risks for senior executives in all organizations, and especially for NGOs, as their work and purpose depend on their reputation. In this work, two indices are proposed, built using novel artificial intelligence techniques to measure the reputational risk of an organization or a group of organizations. The construction of the indices is based on the use of Transformers combined with social network analysis techniques. Results and conclusions from their implementation are presented in an example of X in the case of the conflict between Gaza and Israel.

ABSTRACT. Educational management is a specific field that requires innovative approaches of research methodology to adress the rapidly evolving challenges of the hyper modern education system. This research investigates various methods and the latest trends in research methodologies applied in the field of educational management, with a particular focus on their practical application at Mohamed -V- University. The study aims to examine the researches that have been carried out over the past five years and evaluate the effectiveness and adaptability of these approaches in addressing challenges faced by educational management while also exploring their potential to transform educational management practices. A scientific and bibliometric analysis will be carried out to analyse various articles published in educational management with a focus on national journals, including Moroccan publications and thesis, since the purpose of this research is to explore emerging trends in this field in our country. The current study will focus on approaches such as quantitative, qualitative and mixed methods. The main contribution of this study lies in the need to understand the effectiveness of the operationalisation of methods and methodologies as a way of optimising the resolution of problems in the educational management. It also aims to conduct a better understanding of methodological trends in educational management and their relevance in the academic context.

ABSTRACT. This paper examines the changing terrain of contemporary sociology in Morocco, providing a thorough examination of its fundamental concepts, approaches, and methods. It delves into how sociological research has adapted to Moroccan society's unique cultural, political, and economic contexts by revisiting the foundation and emerging issues within Moroccan society. Key themes include the impact of globalization, social stratification, gender dynamics, and urbanization. The paper also highlights the variety of research methods employed by Moroccan sociologists, spanning qualitative ethnographic investigations to quantitative polls and mixed-method studies. By providing a critical overview of current agendas, it aims to highlight the contributions and challenges of Moroccan sociology, fostering a deeper understanding of its role in shaping both academic discourse and public policy.

ABSTRACT. Morocco's university dropout rate continues to rise, with around 49% of students leaving university before graduating, despite consecutive reforms and measures taken to achieve Morocco's 2015-2030 strategic vision in the higher education sector “For a university of equity, quality and promotion”. This raises questions about the state of knowledge about social inclusion at university, capable of informing decision-making and achieving this strategic vision. Whereas previous studies have mobilized a quantitative approach, but with exploratory aims, to identify the main factors affecting student inclusion on university campuses. A knowledge that we consider unsatisfactory for creating general and regular knowledge beyond the cases studied, no study has chosen a mixed approach to create knowledge on the factors enhancing the attractiveness of the campus environment. Which brings us to our central question: How does a mixed approach contribute to the creation of general and regular knowledge about the factors enabling student inclusion in the campus environment? To answer our central question, we intend to discuss the external validity of future studies that will focus on the inclusiveness of the campus environment, mobilizing both a qualitative (interpretive descriptive research, phenomenology, ethnographic approach, case study) and quantitative approach pursuing a descriptive (Partial Least Squares-based Structural Equation Modeling 'PLS-SEM') and explanatory (Covariance-based Structural Equation Modeling 'SEM-CB') research purpose. From a scientific perspective, this discussion will encourage researchers to choose a mixed approach, with a view to creating regular and general knowledge, participating in this way in the construction of theories on the university's social inclusion. From a managerial point of view, this discussion will highlight the benefits of a mixed approach to framing future higher education reforms and decision making, enabling optimal resource allocation as a result, capable of creating an environment conducive to teaching and learning within universities, prioritizing efficiency over organizational isomorphism.

ABSTRACT. Metacognitive skills are essential for cultivating self-regulation, critical thinking, and continuous learning, all of which are foundational for effective managerial work. The study is designed to propose a MEQue methodology for metacognitive errors measurement. The main research objective is to verify the suitability of the proposed questionnaire containing 33 self-assessment statements aimed at identifying metacognitive errors among managers. The research sample consists of 367 managers, of which 213 (58.04%) are male and 154 (41.96%) are female, aged between 24 and 59 years. Factor analysis enabled extraction of 6 factors characterizing metacognitive errors of managers and labeled as follows: Selective abstractions, Dichotomous decision-making, Negative emotional expectation, Elimination of the positive, Unreasonable generalization, and Ability to read thoughts. The study provides an overview of the applicability of the MEQue methodology, particularly in managerial practice.

ABSTRACT. Composite indicators simplify complex phenomena by combining multiple dimensions into a single score synthesizing the overall latent status, such as gender equality or economic development. These indicators are built on a hierarchical basis and comprise various domains and subdomains, each capturing different aspects of the assessed concept. For example, the European Gender Equality Index (GEI) combines data across six domains to provide a score reflecting gender gaps in a Country. This paper studies composite indicators in a multivariate statistics framework introducing a statistical learning approach for gender gap measurement, that can complement and enrich a composite indicator. Object-Oriented Bayesian Networks (OOBNs) are employed. OOBNs are an extension of Bayesian networks (BNs), namely multivariate statistical models encoding variable relationships through a Directed Acyclic Graph (DAG) and a joint probability distribution. A graph is a mathematical object composed by a set of nodes and a set of edges. Each node is associated with a variable of interest and edges constitute the relational structure between variables. The absence of an edge between two nodes indicates conditional independence between the corresponding variables. OOBNs allow for hierarchical definition and construction of BNs. Their architecture is particularly useful for managing large and complex domains, especially when modular structures are present. Since composite indicators have a clear hierarchical architecture, OOBNs represent a natural tool to model and build them. OOBNs allow for transitioning from computing a GEI score to learning a statistical model that accounts for the relationship between the variables involved in the computation and enables prediction. Here, this methodology is applied to provincial-level data from Italy. Thanks to the inferential engine associated to the OOBN, different scenarios can be simulated in real time, allowing an ex-ante evaluation of the impact, on the GEI indicator and its distribution, of possible actions aimed at gender inequality reduction.

ABSTRACT. A team can be understood as a group of individuals working together towards a shared goal, characterized by a degree of stability while interacting and coordinating their efforts. However, the nature and outcome of teams varies depending on their structure, temporal boundaries and the mechanisms regulating their functioning. In the context of Wikipedia, teams are not always explicitly defined or prescribed; rather, they emerge dynamically through collaboration on articles, discussions, and other editorial activities. We conceptualize Wikipedia teams through multiple registers: (1) regulation, which encompasses the formal and informal rules that govern interactions and shape long-term collaboration; (2) production, where a team contributes to the creation and improvement of content, akin to a collective production process; (3) interaction and communication, which define the intensity and nature of engagement among contributors; and (4) entry of new participants and controversies, which may redefine the team's composition and direction over time. In this context, we aim to operationalize teams within Wikipedia by analyzing patterns of co-editing, discussion participation, and revision activities. We rely on Wikipedia Dumps, which are periodic snapshots that capture revision history, user activity, and edit metadata while omitting article text. Rather than assuming fixed team structures, we adopt a dynamic perspective where teams can be seen as evolving networks of contributors interacting within specific timeframes. By constructing co-editing graphs, where users and pages form nodes and revisions create edges, we can identify clusters of collaboration, measure their density, and track their evolution over time. Additionally, we will examine how coordination occurs beyond direct interactions—through shared project goals, implicit regulatory mechanisms, and task-oriented structures. This approach allows us to explore both the formation and regulation of teams, as well as their impact on content quality and platform governance.

ABSTRACT. This paper presents the initial findings of the Italian PRIN HEALING Project (https://prinhealing.unimi.it/), which investigates the role of social networks in shaping health-risk behaviours and lifestyles within a small municipality in the Lombardy Region of Northern Italy (about 1,500 inhabitants). While existing literature highlights both structural factors (such as education and occupation) and relational factors (family and peer networks) as determinants of health, this study seeks to deepen understanding of how these factors interact and collectively influence health-risk behaviours. Structural factors are relatively static over an individual's life course, whereas social networks are more dynamic, with relationships such as friendships and acquaintanceships shifting across occupational and educational boundaries.

Key research questions include the clustering of health-risk behaviours among interconnected individuals, the comparative impact of structural and social networks on unhealthy lifestyles, and the dynamics of habit transmission within these networks. A clearer understanding of the relationship between stable structural factors and fluid relational dynamics can help enhance public health interventions by identifying influential individuals or communities that spread unhealthy practices.

This research is innovative in its approach to mapping the complete social network (not only egocentric) within a local community to examine health-risk behaviours—an unprecedented method in Italy. Internationally, the Framingham Heart Study offers a similar socio-epidemiological model (Christakis & Fowler, 2013).

ABSTRACT. This paper investigates whether network analysis can provide insights into survey non-response and attrition among young adults (ages 16-30) in a longitudinal household panel study. Non-response and panel attrition are challenges for maintaining data quality in longitudinal studies. First, panel attrition might bias survey estimates if those who drop are different from the panel members who participate. Second, attrition reduces the available sample size of panel members who responded to all the waves, which is required to conduct longitudinal analyses (Lynn, 2018). The challenge of attrition is even greater among young adults (16-30), a population sub-group that is fundamental for the continuity of the study. However, only a few studies have addressed the response of young adults in household longitudinal studies (e.g., Parutis, 2023). Using data from the UK's Understanding Society, we examine the transition to adulthood when they are asked to complete an adult questionnaire. This is accomplished by employing evolving graphs of the variables that influenced attrition in successive waves of the longitudinal study. The findings have implications for survey methodology and the design of targeted interventions to enhance data quality.

ABSTRACT. Soft skills, such as communication, collaboration, leadership, problem-solving and emotional management, are increasingly recognized as essential for both educational success and professional development. Scholars have shown that peer interactions not only influence educational choices but also contribute to the development of social and personal skills. Hence, a social network analysis perspective provides valuable insights into how student connections facilitate (or hinder) the acquisition of soft skills at school. Within this scenario, the present contribution aims at exploring how individual soft skills are affected by peers across different types of social relationships. Primary data gathered in the academic year 2024–2025 through a survey on a sample of high school students in the Campania region are analysed. A proportional quota sample of 28 schools was reached out of a total of 324 schools, and around 1500 students attending the last year took part to the study. A whole network design was adopted to explore multiple dimensions of social interactions in the school context, with a particular focus on identifying different forms of social support. Among the other sections, the questionnaire includes the 3SQ psychometric scale validated in related studies, measuring ten dimensions (among others, trust, empathy, leadership, openness, collaboration, and autonomy). Furthermore, participants were also asked to identify at most five different classmates those they considered their best friends, those who provided academic support in school related-activities, those they turned to for personal advice and those with whom they discussed future plans and options. This allows for the construction of four distinct networks within each classroom. To measure the effect of peers’ on individual soft skills, network models are applied taking into account how different types of interactions and social exchanges at school contribute to explain the development of specific competencies.

ABSTRACT. Research on children’s participation often focuses on legal frameworks and adult-led interpretations, while children's own perspectives remain underrepresented. This study, conducted as part of an ongoing PhD project, explores how children under the age of ten experience and perceive participation within residential care settings. The research applies a mixed-methods approach, combining qualitative content analysis of institutional frameworks with empirical data collection through symbolic interviews and photo walks. These participatory methods aim to capture children’s views beyond verbal expressions, allowing them to represent their lived experiences through images and symbols. This paper critically reflects on the methodological and ethical challenges in conducting participatory research with children in vulnerable contexts. Key considerations include gaining access and consent, ensuring meaningful engagement, and balancing protection with autonomy. While data collection is still in preparation, preliminary insights from the study design and initial phases of engagement highlight both opportunities and limitations of visual and symbolic approaches in childhood research. By focusing on the perspectives of children in care, this research challenges adult-centric narratives and contributes to a broader discussion on how to develop inclusive and emancipatory research methodologies. The findings will provide valuable insights into how research methods can be adapted to foster authentic participation and representation of children's voices.

ABSTRACT. Online gaming platforms constitute unique field sites for researching different themes related to digital youth culture such as play, learning, socialization, and consumption. However, they pose methodological challenges for sociocultural digital media research. This paper introduces the play-along method, inspired by the 'media go-along', “scroll back” and 'app walkthrough' techniques, which involves the informant logging onto and playing a game in the presence of the researcher while they engage in a discussion about aspects of the game that unfold on the screen. By observing and participating in gameplay, researchers gain insights into player agency, game mechanics, and consumption practices within virtual worlds. Carried out across three research projects involving 60 young informants aged 10-24, the method offers several advantages: immersion in the gaming context, and a flexible, informal interview setting. It provides a unique opportunity to observe real-time interactions, digital purchases, relevance of devices, affordances and design, and relational dynamics. However, the method also presents challenges, such as gameplay interference, parental restrictions, and technical issues. Ethical considerations include maintaining the privacy of third parties and managing the blurred boundaries between the informant's private and research contexts. Despite these challenges, the play-along method represents a significant methodological advancement for exploring key aspects of contemporary children’s digital cultures such as interfaces and infrastructures, bodies and affects, memories and narratives, and play and collaboration. The method's participatory nature positions informants as experts in their own lives, providing rich, authentic insights into the commercial and social dimensions of online gaming and contributing to the growing literature in social science and digital humanities methods.

ABSTRACT. Research with children moving alone highlights the importance of adopting innovative and intercultural approaches to understand their experiences of mobility, growth, resilience, and learning. These children cross both visible and invisible borders (Khosravi, 2010), facing inequalities and stereotypes that reduce them to "young adults to be controlled" rather than minors to be protected and valued (Santagati et al., 2024). Despite the highly conditioning system and the presence of vulnerabilities, recent international literature has begun to highlight the strong agency expressed by these minors (Cardoso, 2017). In this context, the research aims to explore how children moving alone perceive and define borders and what debordering and learning processes emerge along these migratory trajectories. To answer these questions, participatory and creative research methods are employed, allowing for the deconstruction of predefined categories, challenging adult and colonial narratives (Freire, 2022), and collecting biographical narratives through an approach that promotes emancipation and active participation. The importance of emancipatory intercultural competences (Aguilar Idáñez, Buraschi, 2023) is crucial in this type of research, as it enables researchers to operate in diverse cultural contexts and address asymmetric power dynamics, creating spaces for social justice. Intercultural competences are not only about having a positive attitude towards diversity but also involve the ability to understand the complexity of situations and manage conflicts effectively. The use of creative and visual methods allows for overcoming traditional data collection approaches and engaging with the emotional and subjective dimensions of children moving alone, revealing their resistance and learning processes in relation to social boundaries. These approaches not only facilitate a deeper understanding of children’s words but also help build a more authentic and respectful narrative of their life experiences.

ABSTRACT. Young people have a lot to say about their lives if adults would only listen. This is the core premise to this paper, which details work the author did in supporting a youth action research team in conducting mixed methods research on their experiences of burnout in secondary schooling. I first present a conceptual framework for understanding the different levels of involvement and leadership of youth in research including youth participatory action research (YPAR). This conceptual framework is important because not all YPAR or youth-involved research is youth-led. Youth-led research refers to research projects where young people take leadership, ownership, and responsibility in most if not all aspects of the research project from topic selection, setting research questions, designing the project, collecting data, analyzing and interpreting data, and presentation (Anselm et al., 2020; Branquinho et al., 2020; London et al., 2003; Ozer, 2017; Ozer & Wright, 2012). Youth-led is an important framing to use because rather than “giving voice” to them (Liebenberg et al., 2020), it creates a space for young people to enact their agency (Bautista et al., 2012; Cahill et al., 2008; Rodríguez & Brown, 2009). Next, I outline the study the youth conducted, which included online and live quantitative survey responses, researcher self-observation and journaling, individual and focus group interviews, and research team notes and debriefing discussions. Then, I describe how I framed my own facilitation as an external research partner and the coaching I provided to other adults working with the group to ensure the project remained youth-led. This work entailed not only teaching youth and adults about the YPAR process but also engaging in ongoing critical reflection on the impact of adults in decentering youth decision-making and ownership of the project.

ABSTRACT. The purpose of this PhD project is to explore and understand through children’s narratives, how their culture is constructed through the entanglements they have with human and more-than-human entities. This presentation will report findings from ethnographic research done with children aged 6 to 8, living in a Casa Hogar or residential care center in Chihuahua, Mexico; using creative methods (drawing and social mapping) and work with children. This research will see children's culture as an entity itself, that is, with different ontological assumptions. In this case, considering that culture is developed among the entanglements of humans and more-than-humans. Subsequently, through a post-human lens, this research will attempt to explore children’s culture while looking into the characteristics of the entanglement children have in their environment for the construction of culture that they make when interpreting ‘their world’ impacted by violence. This, while acknowledging how we are all part of these worlding and common worlds to explore these assemblages and shared agencies in the construction of children’s cultures. This research will use a relational ontology because it allows to understand knowledge as constructed in the relationships between elements.

I propose that there must be an exploration of the mutual response of agencies for the production of children’s culture, as these interactions are what develop a culture (Hengsr, 2005). And these mutual responses are present in the dynamic and transformative entanglements between people, spaces and artefacts present in children’s culture. In addition, the research explores the culture of children living in a context of violence in Chihuahua, Mexico. As cultures exist in interrelated contexts, it is important to analyse whether narco-cultures also come to relate to and impact children's culture.

ABSTRACT. This paper presents the main stages in the legal philosophical and legal sociological thought of Renato Treves, whose contribution to the sociology of law was not only enormous but is also still highly relevant for the present age. It will highlight his interest in the sociology of law, which led him to found an important school of legal sociology and to establish the first academic chair in sociology of law in Italy. The paper will start by setting out the various stages in his thought, including in particular the early period before his exile in Argentina, followed by the Argentine period from 1938 to 1947 during which he started to analyse the relationship between law and society, which subsequently provided the necessary basis for his legal sociology. It will then analyse the long period from 1947 to 1992 during which Treves revived his interest in philosophy of law, while also pursuing his research in the social sciences. A particular focus will be placed on the period from 1959 to 1969 during which Treves pursued his interest in empirical research into sociology of law. This eventually led him to the creation in 1969 of the first chair of sociology of law at the University of Milan, as well as a number of in-depth studies brought together in major publications in this area in 1977 and in 1980. Finally, it will consider the final, long phase of his intellectual development which lasted from 1979 until 1992. During this time he brought together the various strands of his empirical research, having particular regard to the methodological problems inherent within it, as well as his sociological theory, which resulted in the publication in 1987 and 1988 of his magnum opus Sociologia del diritto.

ABSTRACT. This paper explores the significance of adopting a decolonial methodological perspective in the study of deviance and law, emphasizing participatory research practices within international and cross-cultural contexts. It critically reflects on researchers’ positionality and privilege, highlighting the necessity of challenging dominant Eurocentric epistemologies by centering marginalized voices as co-creators of knowledge. The aim is to explore how an intersectional, collaborative, and inductive research approach— grounded in participatory practices that reflect the epistemologies of research participants—can be applied to the study of deviance and law. The paper focuses primarily on the opportunities participatory approaches bring to research, including centering the knowledge and priorities of those most affected by the research and challenging unequal power relations. Participatory approaches provide deeper insights into local dynamics of norm enforcement and resistance among marginalized and invisibilized populations. However, several barriers to the implementation of participatory designs exist, particularly in formal academic contexts, alongside ethical challenges and risks. These include institutional expectations of individual authorship in academic programs, the difficulty of clearly defining research aims and methods due to participant negotiation, extended timelines for achieving consensus, risks of exacerbating internal community power dynamics, ethical issues related to data ownership and interpretation, and the practical necessity of integrating participatory methods with other research approaches. Considering these epistemological, practical, and ethical constraints, this paper interrogates to what extent participatory approaches can effectively be employed in sociology of law and deviance studies and which ones might be most appropriate.

ABSTRACT. In the socio-legal field, the concept of legal culture has been regarded as a key analytical tool and widely applied, yet it has also faced criticism and rejection. Two fundamental issues stand out. The first concerns its internal coherence and viability for empirical research. The second relates to its frequent role as an explicans—whether in explaining individual behaviors or differences between legal systems—while it is far less often treated as an explanandum. This raises a crucial inquiry: how does legal culture take shape, what are its roots, and how does it evolve over time? To engage with these questions, this paper rethinks the concept of popular legal culture, first introduced by Lawrence Friedman and now central to the established research area of Law and Popular Culture. By popular legal culture, we refer to both the ideas and attitudes about law held by ordinary people and the segment of mass culture that engages with law and the legal professions. The paper argues that a sociological study of law should empirically explore the mutual influence between these two dimensions, inherently considering their interconnections with legal norms and institutions on one side and individual behaviors on the other. Building on this argument, the paper pursues two main objectives. First, it seeks to outline the theoretical and methodological debate within Law and Popular Culture studies, including its links to popular criminology, by presenting key insights and critical perspectives. Second, it examines the principal research strategies and the most widely used methodologies in the field.

ABSTRACT. The purpose of the research is to understand how the legal and judicial practices in two Amazonian municipalities (Apuí and Lábrea) respond to the dynamics of environmental crimes in the region. The research project is a based in a qualitative and quantitative methodology. The qualitative methodology (Denzin & Lincoln 1998; Denzin 2009; Loafland et. al. 2005) supports the semi structured interviews conducted with criminal justice professionals dealing with environmental crimes in the state of Amazonas. Several interviews were gathered in the cities of Manaus, Labrea and Apuí, between 2023 and 2024, involving Judges, civil servants, law enforcement from the Amazonas State and federal State. A mix of quantitative and qualitative methodology supports the parallel acquisition of rappresentative cluster of criminal sentences about environmental crimes issued in the Lábrea and Apuì districts. Sentences constitute an important object of socio-legal analysis, given their significance as outcomes of a decision-making process regulated by a particular combination of procedural and material norms (De Felice and Giura 2016). The court decision is a relevant instrument for understanding how the judicial system addresses the challenges tied to environmental crimes (Giura 2015). By the criminal sentences’ analysis become possible to answer several research questions: the structure of legal proceedings concerning environmental crimes and in which way those facilitate responses to criminal events within the two Brazilian cities; who are labelled as criminals what are the economic, social, and legal features of the environmental crimes observed from the gathered ruling; how long lasts a lawsuit for environmental crime originating from those cities? To reach the goal, the criminal rulings have been submitted to analysis exploiting LiGRE software to code qualitative data gathered from the content of sentences issued in Lábrea and Apuì by Criminal Courts.

ABSTRACT. The digital turn has transformed public discourse analysis, offering unprecedented opportunities to examine contested framings in global political narratives. This study applies a mixed-methods approach to investigate German and Chinese public discourses on BRICS from 2021 to 2024, integrating computational text analysis with qualitative frame analysis. The research critically examines how media, institutional elites, and public voices construct strategic framings of BRICS and its member states, revealing underlying epistemological and ideological divergences. Methodologically, this study employs digital methods such as web-scraping, topic modeling, and sentiment analysis to quantify trends in German media and public perception, juxtaposing these findings with critical framing/discourse analysis. The German media landscape is mapped through sentiment trends and lexical shifts, while Chinese state media responses are analyzed through reflexive dialogue, revealing how narratives are shaped, countered, or reinforced. Public discourse is further examined through digital ethnography on social media platforms, providing a grassroots perspective that contrasts elite-driven narratives. This mixed-methods framework addresses key challenges of the digital turn in social research. It demonstrates how digital traces, while expansive, necessitate methodological triangulation to capture contextual nuances. Moreover, by positioning the researcher within this reflexive process, the study highlights the epistemological implications of studying digital discourse in multipolar geopolitical contexts. The findings contribute to critical digital sociology by illustrating the entanglement of media, power, and public opinion in shaping global political imaginaries.

ABSTRACT. We are living in a historical period in which technological innovation is much faster than any other field of study. This digital revolution leads us to think of a transversality on multiple levels of action: from the use of tools that are as innovative as they are unknown in their technicalities of analysis, to the correct use of a wider range of action in a research design that uses mixed methods. In particular, artificial intelligence (AI) offers a series of reflections and opportunities that are unexplored to date. If on the one hand we can think that it is a tool of great utility that will touch a large part of our lives, consciously and unconsciously, on the other hand we ignore the procedures and methods with which AI moves with great adaptive capabilities on our devices. The abstract aims to highlight what contribution artificial intelligence can make to the field of social research by placing as a fixed point the tools consolidated to date in research methodology, whether they are traditional or closely linked to e-methods. It will be an opportunity to compare research carried out with mixed methods on a well-defined target group, celiacs, with research carried out on the same target group but exclusively through the use of Artificial Intelligence. Traditional tools will be directly compared with more innovative ones, including chatbots, in order to define the limits and advantages of a technological innovation with which research methods struggle to keep up with the times. We will see how the results will differ from each other, or if they will have points of contact, not only with regard to the more content-related aspect, but also how the analysis techniques can talk to each other.

ABSTRACT. We are living in a digital age where digital technology provides social science scholars with new tools that complement traditional instruments to support their research activities. The article “Digital Economy Transformation and Social Mobility of Ho Chi Minh City Workers” was developed using Mixed Methods Research (MMR), integrating digital tools into this study. Specifically, VOSviewer version 1.6.20 was used to create maps based on global academic documents and visualize the academic context during the literature review. Quantitative data were synthesized from official statistical websites, then identified macro factors affecting workers' social mobility. Qualitative data were collected through in-depth interviews conducted both face-to-face and online. These interviews aimed to reflect the depth of statistical data and interpret the multidimensionality of practice. In developing this MMR, we prioritized methodological coherence, data quality, and validity throughout the data collection and analysis process. A key implication of this article is its discussion of the advantages and limitations of digital tools for studying social phenomena in contemporary contexts, along with strategies to address these limitations. These issues fall within the scope of session 36: Mixed Methods at the Digital Turn: How Digital is Reshaping Mixed Methods Research.

ABSTRACT. This study examines the virtual reality platform VRChat as an emerging social world where bodies, identities, and relationships take new forms. In these spaces, people engage in affective, embodied interactions, navigating both the possibilities and constraints of digital presence. Individuals, their avatars, and the technology itself function as a cyborg entity, where human experience is co-constructed with digital possibility. Conducted by a digital anthropologist under the guidance of mentors specializing in Human-Computer Interaction (HCI) in VR, Perceptual Psychology, and Cognitive Science, this research explores how a digital anthropology perspective can deepen our understanding of habituation, embodiment, and interaction in VR social worlds. At its core, our mixed methods approach examines the ways we can digitalize traditional anthropological methods while also bringing an anthropological lens to digital methodologies, bridging the gap between these fields to better capture the complexity of virtual life.

We are combining methods including participant observation within VR spaces, analyzing text from platforms like Discord and Reddit, and transcribing content from VR bloggers, Analysis through LLM, alongside semi-structured interviews to capture personal experiences. We also bring in an art production analysis lens, looking at avatar creation, world-building, and experience design as creative practices that shape how users construct and inhabit virtual spaces. Working across these different methods allows us to engage with multiple perspectives on immersion and habituation, but it also raises questions about how to bring such diverse data together. This is a work in progress, and as we continue refining our approach, we are not just grappling with methodological challenges but also seeking to broaden how digital anthropology approaches virtual environments within a mixed methods framework. Findings are expected to be finalized in July..

ABSTRACT. Correspondence and audit studies are widely regarded as a “gold standard” for capturing discrimination and bias. However, gatekeepers (e.g., employers) are the analytic unit even though stated implications often center on group-level inequalities. Using the binomial distribution, we show that such field experiments have the potential to uncover applicant-side inequalities and burdens beyond the gatekeeper biases standardly reported by demonstrating that unit-level probabilities do not accurately reflect real-world applicant chances of success. Specifically, applicants from groups facing lower callback rates must submit more applications to ensure an eventual callback, have fewer opportunities to choose from, and face higher uncertainty regarding how many applications to submit. These results reflect several sequential and cumulative stratification processes “real-world” applicants face that warrant attention in conventional reporting. Our approach can be straightforwardly applied and, we show, is particularly pertinent for employment relative to other institutional domains (e.g., education, religion). We discuss the methodological and theoretical relevance of our suggested extensions and the implications for the study of inequality, discrimination, and social closure.

ABSTRACT. Labor market discrimination remains widespread, disproportionately affecting minority groups. Despite policies, disparities in hiring, wages, and career progression persist, limiting social mobility and economic efficiency. In Italy, women face multiple layers of discrimination, deepening labor market inequalities. These biases extend beyond individual disadvantages, reinforcing systemic barriers that hinder inclusive growth.

This study uses a Factorial Survey Experiment to examine how recruiters' characteristics, such as gender, age, and education, influence wage assignments. Traditional research struggles to separate discrimination causes from other candidate-related factors. To address this, we designed a vignette experiment, varying attributes like gender, ethnicity, and qualifications. Recruiters evaluated these profiles, helping us distinguish between discrimination forms. A D-efficient design was applied to optimize the experimental layout, ensuring statistical efficiency and reducing vignette requirements. Our findings reveal that recruiters’ characteristics significantly impact wage assignments, with notable differences based on gender, age, and education. Male recruiters consistently assign higher wages than female recruiters, regardless of the candidate’s gender. Age-related differences also emerge, as recruiters aged 31-50 exhibit the largest wage disparities, while younger recruiters demonstrate more neutral salary expectations. Education plays a mitigating role: recruiters with higher education levels assign more equitable wages, although gender disparities persist.

These results highlight both structural and individual factors shaping wage-setting practices, reinforcing the need for further research into the mechanisms driving these disparities. The interaction between recruiter and candidate gender suggests that wage gaps are not solely determined by candidate characteristics but also by who makes the salary decision. Addressing these biases through targeted policy interventions, such as bias-awareness training for recruiters, could help foster fairer wage-setting practices in the labor market.

Auspurg, K., Hinz, T. Factorial Survey Experiments. SAGE Publications (2014).

Kübler, D., Schmid, J., Stüber, R. (2018). Gender discrimination in hiring across occupations: a nationally-representative vignette study. Labour Economics, 55, 215-229

ABSTRACT. The present proposal intends to discuss the main results obtained within a quali-quantitative research carried out by the University for Foreigners of Perugia (within a PRIN-PNRR shared with other national universities) with the general aim of reconstructing the socio-cultural traits of the communities of Italian emigrants in California, focusing on the characteristics of the personal social networks - maintained/created in the territories of origin/new arrival. Starting from the results collected through the realisation of 1. a web-survey addressed to Italian key-informants who have emigrated to San Francisco and the nearby areas; 2. remote focused interviews and 3. network questionnaire (linked to the application of network analysis), the contribution intends to carry out a methodological evaluation through which to clarify the strengths and weaknesses of the research instruments used, in consideration of the online transposition, in a digital environment, of interactions traditionally carried out in person. Moving in the context of mixed methodology research, the temporal and semantic sequence of the data collection methods (questionnaire, first; focused interviews and network analysis, then), allowed a strategic engagement of the interviewees, moved by the desire to clarify aspects connected to their socio-linguistic biography; to their identity and values experience; to the social and life experiences matured within relational networks where cultural practices and values are at various levels influenced by their Italian origins. Following the web-survey, the remote focused interviews and the network analysis, represent the empirical basis from which many significant methodological observations resulted. The online context in which the interviews were carried out represented, for the interviewees, the symbolic place within which they revived their own experience as Italians abroad, giving back to the research deep and richly detailed narratives; aspects that fruitfully influenced the accuracy of the information gathered.

ABSTRACT. Twenty years ago I was working on a project interviewing people about personal debt. I had carried out one interview in the early morning and arrived at the second location to hear from a woman in her seventies. She explained her husband had been experiencing mental health issues and had, secretly, ordered hundreds of pounds worth of goods on credit. When he died, she was left with the debts, and then a social security benefits error meant she owed the local authority over £1,000. To pay these off she started back to work as a cleaner, despite not being in good health herself. She spoke about her depression and having no-one to talk to or help her. She was under her Doctors care, and on medication, but had not told her adult children about any of this. After the interview I walked out to my car, drove down the road and had to stop. I sat and cried for some time, but had to collect myself to go onto the next interview. The next day I spoke with colleagues about this and slowly, their stories also emerged of experiences they had struggled with. This paper reflects on interviews and focus groups with those colleagues, and on more recent work as co-ordinator of the Researcher Wellbeing Group of the Centre for Applied Social Science at the University of Sunderland, where we have spent the past two years considering Emotions in research, Researcher Wellbeing and how to enhance Research Culture.

ABSTRACT. Qualitative research is inherently emotional. It requires researchers to engage deeply with participants’ experiences, often encountering moments of vulnerability, distress, or intense connection. Drawing from the perspective of the vulnerable observer (Behar, 1996), this paper reflects on the emotional labor of the researcher, emphasizing how emotions shape both the research process and its outcomes. Rather than merely exposing the researcher’s autobiographical horizon, adopting a vulnerable stance entails recognizing how personal subjectivities and positionalities filter one’s understanding of the field. I illustrate these dynamics through two research experiences: one with parents of premature infants, including those who faced perinatal loss or severe medical complications, and another with academic mothers navigating precarious employment—an experience I was simultaneously living. In both cases, moments of simultaneous sameness and difference (Ezzy, 2010) emerged, requiring an ongoing renegotiation of emotional display rules (Hochschild, 1983). These shifts in power and emotional engagement not only shaped rapport-building but also influenced the very direction of the research. By considering how emotions circulate within the research encounter—affecting both interviewees and interviewers—I argue that emotional reflexivity is not only an ethical necessity but also a methodological resource. Building on Douglas’ (1985) call for research as a creative search for mutual self-understanding, I advocate for greater recognition of emotional labor in fieldwork, urging researchers to integrate emotional literacy into methodological training and practice.

ABSTRACT. This presentation explores the complex emotional and ethical challenges faced by researchers conducting close-up studies of far-right movements, focusing on the tensions that arise when engaging with groups whose values, ideas, and worldviews are deeply misaligned with those of the researcher. Through a reflexive approach, the presentation explores the emotional burden of qualitative fieldwork in politically and morally contentious settings, where the act of listening, observing, and interacting can generate discomfort, cognitive dissonance, and moral distress. The first part of the presentation situates the study of far-right movements within the field of social movement studies, emphasizing the methodological dilemmas of qualitative research in such contexts. It examines the affective toll of prolonged immersion in environments where hostility, nationalist rhetoric, and exclusionary ideologies shape daily interactions. What strategies can be adopted to maintain analytical clarity while managing the visceral reactions that arise from engaging with narratives that contradict one’s fundamental beliefs? The second part of the presentation is grounded in my fieldwork on CasaPound Italia and reflects on the emotional dilemmas of studying the far right up close. It discusses the constant negotiation between empathy and detachment, the strain of maintaining relations with participants while internally rejecting their ideological premises, and the ethical questions that emerge when a researcher’s emotional reactions—frustration, unease, even fleeting moments of affinity—become integral to the research process. By centering the emotional experience of the researcher, this presentation contributes to the broader discussion on emotional literacy in qualitative fieldwork.

ABSTRACT. Preterm birth is a traumatic event impacting infant health and family well-being, presenting challenges during NICU stays and the transition home. The e-ParWelB project addresses this by developing a socio-psychological model integrating eHealth tools, social research, and psychological support for parents. The sociological aspect combines narrative interviews with medical staff and ethnography across NICUs in four Italian hospitals.

NICUs are highly distressing environments, as they confront social actors with the imminent risk of infant death or severe disability, disrupting the natural life trajectory. Discussing topics like neonatal mortality creates emotionally intense moments during interviews. This underscores the need for methodological reflexivity in emotionally charged research, recognizing data collection as an embedded, ethically complex process (Dickson-Swift et al., 2007).

Medical professionals create an apparent "normality" in the NICU's challenging environment to function daily. However, pivotal events, like initiating palliative care or a patient's death, evoke deeply disruptive emotions. Reflecting on specific situations or patients often resurfaces these intense feelings.

For external researchers without intensive care experience, initial NICU ethnography can be profoundly shocking, beyond academic preparation. This aligns with Bourdieu’s (1999) concept of participant objectivation, highlighting the need to critically examine one’s position and impact within the field and the research process. The NICU’s emotional intensity demands heightened reflexivity (Finlay, 2002), as the researcher’s emotions, subjectivity and positioning shape the co-construction of knowledge.

In this context, interviews may be not only a part of the information gathering process but also a cathartic moment. They create a shared emotional space where both interviewee and researcher support each other through traumatic experiences. Following the tradition of relational ethnography (Desmond, 2014), it becomes evident that the interview setting is not a neutral space but rather a co-constructed one, where both the researcher and the interviewee engage in an interactive process of meaning-making.

ABSTRACT. Based on a doctoral study and a research project conducted with breast cancer patients from diverse socio-economic backgrounds in France, this presentation explores the interplay between patients’ emotion management and the researcher’s own emotional experience in qualitative fieldwork. Through three cases, it examines how emotions are actively managed, negotiated, and, at times, destabilizing for both participants and the researcher. First, laughter and humor emerge as powerful tools for patients to reframe emotionally charged situations, either as self-mockery or to ease the burden on their relatives and caregivers. Second, some patients engage in comparative suffering, minimizing their distress by contrasting it with more severe conditions. While this fosters resilience, it also reflects a social expectation to endure hardship with composure. Lastly, the withdrawal of a patient-partner from the research project due to emotional exhaustion highlights the limits of engagement in collaborative research when illness-related emotional work becomes overwhelming.

These cases reveal not only the diverse strategies employed by breast cancer patients but also the ethical and methodological challenges for researchers navigating intense emotions in the field. How do we acknowledge and integrate these emotional dimensions into our research practice? What strategies help researchers manage their own affective responses? By reflecting on these questions, this presentation aims to contribute to the broader discussion on emotional literacy in qualitative research.

ABSTRACT. This paper explores the intersection of gender inequality, societal structures, and short-term fertility intentions through an innovative methodological lens, contributing to the broader understanding of gender and political behaviour. Using feminist theories of gender regimes and Giordano’s (2019) classification of European gender regimes (Scandinavian, Continental, and Mediterranean), the study examines how structural inequalities and traditional gender roles shape reproductive decision-making in Finland, Germany, and Spain.

The research employs a mixed-methods design, integrating data from the Generations and Gender Survey (2018–2021) and the Spanish Fertility Survey (INE, 2018). Classification and Regression Trees (CART) are used as a novel methodological tool to identify non-linear relationships and gender-specific patterns of marginalization in fertility intentions. Predictor variables include employment, financial conditions, caregiving responsibilities, gender-related attitudes, and sociodemographic factors. This approach highlights the potential of advanced computational techniques to operationalize gender and uncover complex dynamics in comparative contexts.

Preliminary findings reveal significant gendered disparities in fertility intentions, with caregiving responsibilities and employment being key determinants for women, while financial stability and gender attitudes are more influential for men. Mediterranean countries exhibit higher levels of marginalization among women, while Scandinavian countries, with more progressive gender norms, show higher fertility intentions and reduced inequalities. These findings underscore the importance of interweaving gender-sensitive methodologies with comparative political analysis better to understand the impact of structural inequalities on individual behaviour.

By applying an innovative methodological framework, this research contributes to developing gender-sensitive tools in political and social science research. It offers valuable insights for addressing gender-based marginalization and advancing policies that promote equality in reproductive decision-making.

ABSTRACT. This paper presents the index developed by the authors to measure the gender sensitivity of parliaments. The indicators are based on the institutional feminist definition of gender-sensitive parliaments. The concept of gender-sensitive parliaments refers to a parliament that responds to the needs of both women and men in its composition, structure, processes, and outputs, while seeking to eliminate barriers to women's full participation (Palmieri, 2019: 177). This definition includes key elements such as the balanced presence of women and men, the rules and practices governing parliamentary activity, parliamentary culture, and the legislation and other outputs produced by the parliament (Childs & Palmieri, 2020). In developing the index, three dimensions have been considered: descriptive representation (understood as the proportion of women and men), the substantive representation of women (examined through their role in institutional leadership positions and their promotion of gender equality measures), and an analysis of equality actions implemented at the level of parliamentary functioning. The authors have applied the index to two case studies: the Spanish Congress of Deputies and the Basque Autonomous Parliament. This study builds upon the findings from both case studies and proposes a revision and enhancement of the indicators that should constitute the index. The aim is to enable a more in-depth analysis and, most importantly, to facilitate its use in comparative research.

ABSTRACT. It is increasingly recognised that measuring human and economic development and societal progress solely in terms of income is inadequate (UNDP, 2009, 2010; OECD, 2013a, 2013b; European Commission, 2013; OECD, 2023). While income measures remain significant for various policy purposes, they arguably fail to capture the comprehensive picture of individuals' current and future well-being. The concept of well-being adopted in this article acknowledges the extensive debate regarding its definition (OECD, 2013a, 2013b; UNDP, 1990; Stiglitz et al., 2009; Stiglitz et al., 2018), a discussion that spans from income-based measures to multidimensional understandings of well-being. This approach is aligned with the ongoing efforts to establish, develop, report, and integrate well-being indicators within the budgetary process (OECD, 2023). The framework for measuring well-being developed in this paper draws from the theoretical foundations of objective well-being, particularly the capabilities approach, which was advanced by Amartya Sen and Martha Nussbaum, and combined with insights from theories of subjective well-being. By integrating these two perspectives, incorporating a gender lens, and recognising the necessity of applying the methodology within the budgeting process, we have created a methodological model for measuring well-being. This model has produced a well-being budget indicator, enabling the ranking of public expenditures according to their impact on the well-being of women and men, which can be utilised in the budgetary process.

ABSTRACT. An indicator is defined as a simple and reliable tool for measuring achievements, reflecting the evolution of social change and assessing the impact of actions and interventions. It also enables comparative studies to be carried out and different contexts to be ranked according to the scores obtained. Can women's political participation in peacebuilding processes be measured? If so, what are the elements to be taken into account, and how can different elements be quantitatively weighted to construct a single indicator? Furthermore, are indicators and dimensions used in other contexts of participation useful?

This paper explores this possibility and reflects on the different dimensions that a participation index should have in order to measure this reality in different contexts. This paper is presented within the framework of the activities of the research Project “Women's participation in processes of transitional justice. Peacebuilding proposals in Colombia, Guatemala and Peru - PROMUJER

ABSTRACT. The study of the determinants of gender attitudes has increasingly grown in recent years, with the development of different theoretical explanations. On the one hand, the modernization theory emphasizes the change of values at the generational cohorts, second, studies focus on how the partisan-ideological polarization fuel gender backlash and, on the other hand, a more sociological-economic explanation would point to the sense of threat perceived by out-groups who feel left behind by the advances of feminism. This article aims to test the predictive explanatory capacity of three theories on gender attitudes in three realms: societal, labour and domestic. Using structural equation modelling, we propose to identify key relationships between variables that affect the predisposition to support or reject gender equality. We rely on data from an original survey developed by the UNTWIST project (Policy recommendations to regain ‘losers of feminism’ as mainstream voters. https://cordis.europa.eu/project/id/101060836 ) in six European countries (Denmark, Germany, Hungary, Switzerland, Spain, and the UK).

ABSTRACT. The structure of political conflict in Western European democracies has shifted with the rise of populist parties, capitalizing on the crisis of mainstream representation. Research suggests younger individuals are more likely to support populist parties, yet it remains unclear whether this pattern stems from cohort differences, life-cycle stages, or systemic shifts affecting all voters. Among these, generational differences may have the most lasting impact, as cohort electoral behavior tends to remain stable over time. This is because values shaped through early socialization provide a foundation for political attitudes. To address this gap, this study applies Age-Period-Cohort (APC) analysis across eight Western European countries (2002–2024) using ESS, EES, ITANES, and ELNES data. Findings indicate that the 2008 economic crisis increased populist support across the whole population. However, in some countries, individuals socialized during the crisis are particularly inclined to support populist parties, especially on the left. By leveraging cross-national survey data, this study highlights both the immediate destabilization of party systems and the long-term impact of economic and societal crises on younger cohorts’ electoral behavior.

ABSTRACT. In this contribution, we will present a case study that is based on the integrated use of data from the joint World Values Survey and European Values Study data (joint EVS-WVS 2017-2022 data-set), in combination also with other sources from both other international surveys and non-survey data, such as, for example, the Sustainable Development Goals (SDG’s) database and other indices with nation as a unit of measurement. The utilisation of these data has been instrumental in the construction of the World Love Index (WLI), a longitudinal and transnational index designed to serve as a detection tool of social love as a proxy for social well-being. In our study, we adopt a definition of social love that encompasses four constituent dimensions: overabundance, care of the others and the world, recognition of the other and universalism. This definition involves extensive use of indicators closely related to the concepts of solidarity, environmentalism, gender equality, trust and democracy. Furthermore, during the construction of the WLI, a series of prolonged deliberations were undertaken, in conjunction with an international panel of experts hailing from a multitude of culturally diverse backgrounds, concerning the enhancement of the comparability of the data derived from the surveys, which, although also collected at a global level (in particular the WVS), are based on a purely Western view, both as regards the content of the questions and the methods of answering them, and as regards the method of survey used, specifically the use of a structured and standardised questionnaire. As a result of our reflections, we have explored several options which, although they do not resolve the issue of intercultural comparability at its roots, may offer a more informed interpretation of this bias.

ABSTRACT. Secularization theory suggests that religiosity declines over time, yet the study of religious change across countries faces a critical challenge: the potential noninvariance of religiosity measurement. Previous research has indicated that measures of religiosity are culturally specific, raising doubts about the universality of religiosity and its measurement across diverse countries. Nevertheless, it was demonstrated that religiosity measures can achieve approximate invariance across some European countries. However, whether these measures are invariant not only across countries but also over time has yet to be investigated. Without temporal invariance, observed changes in religiosity may reflect shifts in the understanding of religiosity and its measurement, rather than true societal trends, thereby undermining the validity of comparisons over time. This study examines the measurement invariance of religious involvement (RI)—captured by the frequency of an individual's religious attendance, frequency of praying, and self-assessed religiosity indicators—across 11 rounds of the European Social Survey (2002–2024). Using a one-factor model of RI and the alignment method, we find that while exact invariance across rounds is largely absent, approximate invariance holds in all countries, providing reliable, aligned factor means for assessing trends in RI in European countries over time. Further analysis reveals patterns of religious decline across Europe, while some countries exhibit stable or even increasing levels of RI, diverging from the overall trend. Additionally, we discuss the polarization of countries based on the varying dynamics of their RI and provide several possible explanations for the divergent trends.

ABSTRACT. Sensitive topics pose a challenge in social science survey research. In this context, various techniques have been developed to assess sensitive issues, such as the randomized response technique, the sealed envelope method, or wording and framing techniques. However, some of these techniques are unsuitable for online surveys. In our study, we tested the direct and indirect measurement of experiences with racism and subsequently conducted a comparative analysis of these two measurement instruments. These instruments were applied in the context of a large, probability-based survey on the integration of migrant women in Germany, the so-called "DeZIM.panel." The aim was to determine the extent of racist experiences using both instruments and to identify differences in respondents' answers. Our descriptive findings indicate that the instruments yield different prevalence rates, with the indirect instrument reporting a higher prevalence. Furthermore, multivariate analyses aimed at explaining these differences reveal that men, younger respondents, and migrant women are more likely to report racist experiences using the indirect instrument, whereas respondents' educational levels had no discernible impact on the measurement.

ABSTRACT. Focus groups are used for qualitative research, with rules governing their use. Some literature advises against their use in studies on sensitive issues. This communication is based on the use of focus groups to study social representations of students at the University of Coimbra regarding sexual harassment. This method was chosen mainly because of the advantages, such as the speed of the information-gathering process and its richness in better understanding the attitudes, beliefs, and feelings of the participants. Another aspect was the use of group interaction to avoid individualizing the problem and the risk to become a moment for denouncing these behaviours, and to access the way in which the phenomenon is socially constructed. However, it is linked to practices, private experiences, values, and romantic/sexual histories that are difficult to share in a group context. This method was applied in mixed-gender and in exclusively male and female groups. In all of them, very different themes emerged, and the comfort level varied. I had access to a variety of opinions, and I found that being in a group made some participants feel more comfortable. In a way, it ended up becoming a moment of collective learning and understanding of the dimensions of sexual harassment. One disadvantage was the resistance to talking about personal experiences, and, at a time when awareness of the problem was growing, this topic was very sensitive for many students. I reduced the number of participants (5-6), but this impacted the fluidity of the discussions and the interaction, which was more restrained compared to moments when the topic was glossed over or barely discussed. The context of hyper sexualization in academia was addressed more than the experiences of violence, which hints at the normalization of sexual harassment, but this cannot be understood as such.

ABSTRACT. Loneliness in general amongst youth is an underresearched topic in certain aspects. For example we have some knowledge about incels and about loneliness amongst young people who live with mental helath issues, but we lack general knowledge about loneliness amongst young people. If we examine the data of the Hungarian Youth Research 2020, we can see that amongst the hungarian youth, 25 precent of the 15-29 year olds has never had a serious relationship and 17 percent of them have never been on a date before (Tóth – Fekete – Nagy, 2022). Loneliness in general is a is a sensitive topic which is not easy to research, and it can also lead to social isolation which is a private matter. How can we recognize loneliness amongst youth and what kind of challenges and opportinities we have to conduct a research amongst the students at the University of Szeged? In my presentation I would like to describe the process of our research – e. g. the challenges of the conceptualization process and to find the best methods to collect data.

ABSTRACT. Social and cultural norms experienced during formative years, alongside socialisation experiences within the family of origin, play a crucial role in shaping individual perceptions of the future, personal expectations, and life choices. As Italian society undergoes profound transformations in terms of social norms, cultural values, and demographic and family behaviours, it is essential to explore how these changes influence younger generations. This study aims to investigate the expectations of young adults concerning family structures and personal relationships as well as how these perspectives are shaped by their past experiences of socialisation. It also addresses the role of cultural and societal shifts in defining relational norms and aspirations. To achieve these objectives, a qualitative approach will be employed using focus groups as the data collection method, involving young Italian people aged 20 to 29. Focus groups will facilitate open discussions, enabling participants to express complex thoughts and personal values that might not emerge in surveys or interviews, making them ideal for exploring topics like family aspirations and future relationships. Topics of discussion will include how young people imagine their future family lives, whether they anticipate forming traditional family units or alternative arrangements, and what factors influence these expectations. Given the sensitivity of the topics discussed, the focus groups will be conducted in a safe and non-judgemental environment to ensure participants feel comfortable expressing their views and experiences freely. An in-depth analysis of these discussions, employing an inductive approach, will identify recurring themes and relational patterns, offering valuable insights into how family background and personal experiences influence young adults’ visions of future relationships. The findings will contribute to a broader understanding of how evolving social dynamics shape the way young people envision their personal relationships and family lives into adulthood.

ABSTRACT. This paper presents Large Language Models (LLMs) that leverage data from the Manifesto Project and other expert surveys to distinguish three political dimensions within the texts of political parties around the world. It focuses on identifying populist versus non-populist stances, ideological positioning, and liberal versus illiberal characteristics. The models can analyze texts in more than 30 languages. They achieve an accuracy of nearly 90% for detecting populist stances and liberal/illiberal characteristics, and over 90% for identifying ideological positioning. However, accuracy varies across languages, with English and Spanish yielding the highest accuracy. This paper highlights the potential of LLMs to meaningfully identify political texts. Moreover, it demonstrates the value of human expert knowledge in training and validating these tools. The models presented have the potential to become a powerful resource for the general public, practitioners, policymakers, and academics seeking reliable insights into the stances of political parties.

ABSTRACT. Many logit types of models are commonly and routinely used in a wide variety of scientific fields such as in social sciences, economics, health sciences, and other fields to model categorical outcomes. Some common types include binary logit model, multinomial logit model, ordinal logistic regression, conditional logit model, mixed logit model, and panel logit models. Compared with linear models, the direct interpretation of coefficients from logit models is generally much less straightforward and much less accurate. Logit models are usually interpreted using one or two following methods: odds ratio, marginal effects, predicted probabilities, and microsimulation. In this project, we aim at accomplishing four objectives. First, we provide a description of the microsimulation approach as contrasted to the other interpretation approaches. Second, we demonstrate the procedures how microsimulation could be implemented in STATA, R and SAS using data examples. Third, we experiment with AI tools for microsimulation and compare the processes and the results with the traditional way of conducting microsimulation. Four, comment on the usefulness of AI tools for data analysis.

ABSTRACT. Our study’s main contribution lies in generating new knowledge about the use of AI among PhD students and early-career researchers in the social sciences. While most studies focus on AI’s role in specific disciplines—such as psychology, health sciences, administration, and education—or in discrete academic tasks like literature reviews and scientific writing, our research takes a broader, PhD-centered, multinational, and multidisciplinary perspective. We explore how researchers approach and select AI tools, how they interact and collaborate with AI systems, and how they integrate these technologies into their workflows to achieve their research objectives. This study integrates Actor-Network Theory (ANT) (Latour, 2005; Callon, 1986) and the Co-Intelligence Framework (Mollick, 2024) to examine AI’s role in academic knowledge production. ANT provides a lens for analyzing AI’s evolving agency, while Mollick’s approach emphasizes experimentation and critical engagement with AI as a co-creator of knowledge. By combining these perspectives, this research examines how AI tools shape knowledge co-creation, research workflows, and epistemic authority within academic ecosystems. We conducted an exploratory survey among PhD students in social sciences in Europe, using a mixed-method approach that integrates quantitative analysis of responses with qualitative critical discourse analysis of the prompts. The analysis of prompting styles reveals varying degrees of agency and roles attributed to AI tools by human agents. We conceptualized four main categories of AI agency, each representing distinct patterns of human-AI collaboration: (1) tutoring/teaching agent, (2) subordinate assistant, (3) cognitive partner, and (4) substitutive partner. AI tools are mainly used for academic writing, with background research and literature reviews as secondary applications. While PhD students rated AI-generated content lowest in originality, they found translation support and writing enhancement most beneficial. Responses suggest a shift toward fluid knowledge creation, integrating human critical thinking with AI’s data processing, highlighting AI’s versatility and the challenges of human-AI collaboration.

ABSTRACT. AI and big data are undoubtedly transforming the landscape of social research (Anderson, 2008). They are offering new and innovative tools for analysing complex phenomena (Airoldi, 2022). Within this context, AI emerges as a tool for researcher empowerment, enhancing both the efficiency and accuracy of analyses (Christou, 2025). This study draws on secondary data from the research Emotional Dynamics in Educational Relationships within Digital Learning Spaces (Sapienza Università di Roma – Scientific Coordinator Veronica Lo Presti) and explores the role of emerging AI technologies in enhancing various phases of the research process. The aim of this contribution is to examine the extent to which emerging AI technologies can be utilized in social research (Bail, 2024) and to assess their potential in terms of methodological innovation and researcher empowerment. The analysis focuses on the benefits of AI, including increased speed and efficiency in data processing, the improvement of research quality by automating repetitive tasks, and the identification of patterns and trends that are difficult to detect with traditional tools (Mazzeo Rinaldi & Occhipinti, 2023). Another aspect addressed is the reciprocal enrichment between social research methodology and other fields of knowledge. This not only expands the researcher's toolkit but also fosters methodological evolution capable of responding to the new challenges posed by the digital era (Addeo, Mauceri, Punziano, 2022). However, the integration of AI into social research raises new and significant methodological and ethical concerns (Giuffrida & Mazzeo Rinaldi, 2020). The study shows that a critical use of AI, when accompanied by ethical and methodological reflection, can have a significant impact on the use of techniques and tools specific to social research. To achieve this, it is essential to adopt an approach that balances technological innovation, research ethics, and interdisciplinary dialogue.

ABSTRACT. Social science research increasingly employs artificial intelligence (AI) to analyse complex human behaviour and social phenomena. However, AI systems have demonstrated particular vulnerability to adversarial attacks, i.e. deliberate manipulations designed to confuse or mislead algorithmic decision-making. We examine how adversarial vulnerabilities create unique methodological and ethical challenges for social research integrity. In social contexts, adversarial attacks may manifest when research subjects strategically modify their behaviour to influence outcomes or when external actors manipulate input data to skew research findings. A critical aspect is data poisoning, where training data is compromised to induce systematic biases, e.g., by exploiting the reality-altering effect of deep-fake content, especially on social media datasets. These vulnerabilities pose significant risks to research validity and reliability. Social phenomena captured through AI-mediated observation may represent strategic performances rather than authentic behaviour. We believe that a combined approach is desirable for addressing these challenges, including: • technical safeguards (including a deepfake detector tool, or adversarial training and robust optimisation) • methodological approaches (such as emphasising triangulation and mixed-methods validation) • ethical guidelines prioritising transparency and participatory design We argue that acknowledging adversarial vulnerabilities strengthens research integrity and offers unique insights into human agency and resistance within algorithmic systems.

ABSTRACT. Computer Assisted Qualitative Data AnalysiS (CAQDAS) tools have been widely used by researchers for over 30 years. Whilst there is great variation across the range of packages available, they have broadly supported the integration, exploration, organisation, reflection about, and interrogation of qualitative materials (Silver & Lewins, 2014).

A number of these software have recently integrated one or more of what can be thought of as five distinct “Gen-AI analytic capabilities”. This paper will describe these five “capabilities”: designed to 1) generate, 2) convert, 3) summarise, 4) converse and 5) label qualitative data (Silver & Wright, 2024). I will then consider how these Gen-AI capabilities might appropriately be integrated into the workflow in relation to contrasting forms of thematic analysis: Boyatzis’ code reliability method, template analysis, and Braun and Clarke’s reflexive thematic analysis. These methods draw on different epistemological and ontological foundations and therefore enable concrete discussions about appropriate use of Gen-AI tools for qualitative analysis approaches along the methodological spectrum. I will give examples from various CAQDAS packages, including MAXQDA, ATLAS.ti, NVivo and QualCoder.

My presentation frames the above in the context of a new initiative from the CAQDAS Networking Project, at the University of Surrey in the UK, which has been providing information, advice, training and support in the use of CAQDAS since 1994. We are developing a store of information designed to foster appropriate use of AI in qualitative analysis. I will finish my presentation by showcasing these resources and highlighting opportunities for researchers to contribute to them as our collective thinking on these issues progresses.

References: Silver C. & Lewins A (2014) Using Software in Qualitative Research: A Step-by-Step Guide, 2e. Sage Publications Silver, C. & Wright, S. (2024). The good, the bad, and the ugly of AI in qualitative analysis. SRA Annual Conference.

ABSTRACT. It is widely agreed that Generative Artificial Intelligence (GenAI) will transform conventional practice across the spectrum of service industries in the near future. It seems unlikely this will exclude survey research. Understanding how to capitalise on this potential is a key priority. The present study forms part of a wider project, funded in the context of the UK's ESRC-funded 'Survey Futures - Survey Data Collection Collaboration' research programme, designed to assess the utility of Large Language Models (LLMs) for improving the quality and cost-efficiency of questionnaire design, evaluation and testing (QDET). The research addresses the following questions: 1) How effective are LLMs at a) applying question design and evaluation frameworks, and b) generating and analysing cognitive interview data, to identify problems with draft survey questions?; 2) What are the optimal ways of fine-tuning and prompting LLMs to match or exceed human performance of QDET tasks?; and 3) Which procedures should be followed to ensure the use of LLMs in QDET tasks optimises survey quality, while complying with legal and ethical frameworks? We present preliminary findings of the first phase of this research, which focuses on the effectiveness of LLMs at applying existing frameworks and checklists in the evaluation of survey questions, and the results of a validation exercise comparing the results of Gen-AI QDET evaluations with those of human coders.

ABSTRACT. This work examines the critical role of ethics in open science, emphasizing its fundamental importance in promoting responsible research practices, transparent knowledge sharing, and meaningful community engagement. Ethical considerations are essential not only for ensuring compliance with legal and institutional frameworks but also for fostering trust among researchers, institutions, and the broader public. By adhering to key ethical principles, open science fosters collaboration, inclusivity and responsible knowledge advancement. Although ethics is fundamental in any research context, it becomes even more critical in projects with high collective value and significant social impact. Open science initiatives often deal with sensitive data, diverse stakeholder interests, and complex governance structures, making ethical integrity a cornerstone of their success. These issues, including informed consent, data privacy and the equitable distribution of research benefits, must be carefully addressed to uphold fairness and transparency. Within this framework, the contribution examines practical cases developed within the FOSSR infrastructure (Fostering Open Science in Social Science Research), focusing on its four main lines of activity: IOPP, GGS, GUIDE, and SHARE. Specifically, it explores how ethical evaluation, proper data management and adherence to ethical standards shape research in these contexts. The analysis highlights key challenges and best practices related to open science, the governance of large-scale demographic and social surveys, the ethical implications of international data harmonization and the responsible management of sensitive survey data.

ABSTRACT. With the Occupation and Competence Radar https://www.bibb.de/en/170512.php, the Federal Institute for Vocational Education and Training (BIBB) is developing an innovative database for vocational education and training as well as labor market development. The Radar differs from other portals in the range of topics covered (e.g. digitalization, green economy, staff shortages, job flexibility and fitting problems, apprenticeship quote, continuous vocational education and training (CVET) opportunities, advanced training courses, job prestige, job exposure and satisfaction, ….) and the possibilities for combining them at sectoral and occupational level. We bring together a wide variety of data sources, from process-produced data, big data (e.g. job advertisements, commercial registers, social media data), to classic panel and trend surveys and qualitative case studies. What these data sources have in common is that they provide differentiated information about the profession and/or demonstrate sector differentiation and are as regionalizable as possible. With the help of the German-Labor Market Ontology (GLMO), the different job titles and classifications can be brought together and mapped to the standardized German occupational classification (KldB) and the ISCO. In addition, the necessary occupational skills and tools can be described and linked to various standards. Missing levels of differentiation are estimated by adjusting marginal sums. The entire data material is shown on the basis of around 1,500 occupations, 63 industries and 16 regions for Germany. With the help of the very differentiated information in job advertisements, we expand the professional information by adding competency requirements from both the job advertisements and the training regulations. The data set is based on the total population of Germany according to the national accounts and has been harmonized with this. This means that an overall macroeconomic model that is also differentiated by industry and occupation can project developments into the future.

ABSTRACT. Historically, Italian social science research communities have struggled with poor research infrastructure and a critical lack of longitudinal data, with profound consequences for understanding and addressing social change. Based on a probability sample of approximately 10,000 individuals aged 18-74, drawn from the national population register, the Italian Online Probability Panel (IOPP) will be the first initiative in Italy to produce high-quality longitudinal survey data monitoring social transformations. IOPP is an open infrastructure, both in terms of input and output, and this represents a significant step forward for the Italian social science community. The panel’s surveys will feature a core questionnaire exploring enduring themes – family and housing, education, work, income, inequality, vulnerability, and political attitudes – and rotating modules aimed at tracking emerging societal issues. Moreover, researchers and their teams will have the opportunity to propose additional modules via open calls to explore topics not included in the core questionnaire or to delve deeper into existing topics. Data will be released through the FOSSR infrastructure, in an open format that complies with FAIR principles. Datasets will be Findable through persistent identifiers (PIDs) and descriptive metadata, Accessible via authentication and authorization systems, Interoperable with other data and tools, and Reusable under an open-access license. The datasets will adhere to international classification standards to ensure comparability with other major European and international surveys. Detailed metadata will provide a comprehensive description of data production and interpretation, ensuring that the data is easily usable by all. Data will be available in two main formats: aggregated data and microdata for research, in compliance with GDPR regulations. By leveraging traditional survey methodologies alongside advanced tools for data maintenance, IOPP represents a transformative step in embedding Italy within the global ecosystem of social science research, while promoting transparency, accountability, and the advancement of Open Science.

ABSTRACT. The growing complexity of research data infrastructures presents both opportunities and challenges for social science research. A persistent hurdle is the burden of repetitive, error-prone data management tasks that consume valuable time and resources. The ‘Data as Code’ (DaC) paradigm offers a transformative solution by applying software development methodologies to research data management. This approach enhances reproducibility, efficiency, and transparency, aligning with the Open Science and the FAIR (Findable, Accessible, Interoperable, and Reusable) principles for digital research infrastructures, thereby fostering methodological rigor and innovation. This presentation explores the integration of programmatic tools, artificial intelligence, and the DaC approach within social science data infrastructures, contributing to ongoing discussions on the future of research data management while providing practical insights for researchers and data archivists to improve data usability and long-term preservation. Through case studies from the Data Archive for Social Sciences in Italy (DASSI) — the Italian Service Provider of CESSDA ERIC — we demonstrate how these methodologies improve data quality, reproducibility, and long-term preservation. By reducing manual interventions and enhancing data curation processes, this approach minimizes human error and bolsters data archiving, accessibility, and interoperability, thereby allowing professionals to dedicate more time to critical, high-value tasks. By embracing the Data as Code paradigm, research infrastructures can move beyond traditional matrix-based data structures, enabling seamless integration and management of diverse data formats.This flexibility ensures that heterogeneous datasets — ranging from hierarchical and nested data to unstructured sources — can be seamlessly integrated, curated, and disseminated, expanding the scope and potential of social science research.

ABSTRACT. The preservation and sharing of social science data is not new, with domain specific data archives operating and developing since the 1970s. Today, 22 Member States and 12 partners are associated in the Consortium of European Social Science Data Archives (CESSDA). Slovenia has been a member of CESSDA since 1997, with the Social Science Data Archives from the University of Ljubljana (ADP) as service provider. ADP provides selection and permanent curation of quality data from the Slovenian research landscape and access to it for the target communities. Research involving sensitive data, e.g. special categories of personal data, is particularly challenging and labour-intensive. In the process of acquisition, ADP determines whether the research meets the requirements of the GDPR and national legislation and checks the potential usability of the data. In doing so, it follows the principle: "open as much as possible, closed as much as necessary". In this presentation, we will describe the process by which the ADP takes over the material from the researcher, verifies compliance with legal requirements, assesses the risk of disclosure of research participants, and applies safeguards such as anonymisation and restricted access to data (e.g. safe room environment). During the process, the ADP carries out an assessment of the quality of the material taken over, taking into account methodology, sampling, integrity of the material, and the potential for reuse by different audiences. Dilemmas and solutions will be illustrated by two international research projects involving sensitive personal data. The social science data archives associated in CESSDA are an important actor in the implementation of the principles of open science and in particular the FAIR principles. The special value for the social sciences is that they ensure the continuous development of infrastructure and services, tailored to the target users, and build high-quality datasets for future research.

ABSTRACT. The contemporary media landscape presents significant challenges for democratic societies, particularly with the spread of fake news and declining trust in science. Traditional media organizations rely on journalistic standards for verification of information, yet the rapid evolution of communication technologies calls for new strategies to combat misinformation. This study explores the role of science communication in fostering public trust, engagement, and resilience against fake news.

While technological solutions such as algorithmic fact-checking dominate current responses, this research shifts the focus to social and human factors. It examines how trust in science can be cultivated through collaborative efforts involving scientists, journalists, and community stakeholders. A discussion paper by the Pan-European Academies (ALLEA, 2022) underscores the importance of scientists actively participating in online discourse to expose and counter misinformation. Addressing knowledge gaps in the effective dissemination of scientific information is critical, as skepticism towards science can negatively affect public health, risk perception, and societal stability.

This study aims to assess the science audience in Lithuania through a representative survey (n=1000), segmenting the population based on cognitive, behavioral, and personality factors. Unlike previous studies that focus primarily on sociodemographic variables, this research identifies stable associations between attitudes toward science, fake news, and media consumption habits. The methodology incorporates tools such as the Swiss Science Audience Cluster Analysis, a German survey on fake news attitudes, and the Big Five-2 personality assessment.

Findings contribute to science communication strategies by defining audience segments and tailoring engagement methods. The results offer actionable recommendations to enhance public trust in science and mitigate the impact of misinformation, ultimately reinforcing democratic resilience and informed decision-making in an era of rapid information exchange.

ABSTRACT. In recent years, mainstream social media platforms have redefined their content moderation policies in response to regulatory pressures, technological advancements, and transformations in public discourse on freedom of expression and misinformation control (Gillespie, 2018). In this context, Meta (Facebook, Instagram, and Threads) has recently implemented a significant reform, replacing traditional fact-checking with the Community Notes system, a collaborative verification mechanism already adopted by X (formerly Twitter) (Vosoughi et al., 2018). However, despite relying on user contributions, this system is regulated by algorithms that determine the selection, visibility, and reliability of the annotations, thus influencing moderation dynamics and the circulation of information (Napoli, 2019). This change raises questions about its effectiveness, compliance with the European Union’s Digital Services Act (European Commission, 2022), and its broader implications for online public discourse (Zuboff, 2019). Given these premises, this study examines user perceptions of the introduction of Community Notes through a comparative analysis of comments generated on Mark Zuckerberg’s Facebook and Instagram posts related to this policy change. The objective is to assess the extent to which users support or oppose the new model and identify the main arguments emerging in the online debate. This research adopts a qualitative approach based on digital ethnography (Sumiala & Tikka, 2020) and systematic content analysis. A total of 1,000 comments from Facebook and 1,000 from Instagram will be manually collected and categorized using NVivo software according to the following parameters: stance on the change (supportive, opposed, neutral), type of argumentation (epistemic, ideological, experiential, technological, comparative), comment tone (constructive, adversarial, ironic), and engagement metrics (number of reactions, replies, and shares). The comparative analysis will provide valuable insights into the differences between the two platforms and the role of collaborative moderation in balancing freedom of expression with the need to counter disinformation.

ABSTRACT. The concepts of “fake”, “disinformation”, “misinformation”, and “propaganda”, as components of the Disinformation Study, have become firmly established in everyday vocabulary not only in the journalistic community and among media experts, but also in a much wider audience. These concepts are partly perceived as synonymous, although each has its own characteristics, nature, and consequences. For example, fakes concern the unreliable information to disinform the audience. It has a large number of subspecies and can be classified according to several features: form, scale, consequences. Media literacy presents an important soft skill for all Internet users, but for Ukrainians, it becomes much more important - the country has been in a state of full-scale war for the fourth year. Thus, information security presents an extremely important component of national security especially in wartime. So the Internet with social media is a battlefield, a confrontation with the aggressor country. Along with the unprecedented opportunities that the network provides for information and communication, a number of threats arise: - the spread of hostile narratives to Ukrainian and foreign audiences; - the spread of fakes, and disinformation; - the publication of the consequences of enemy shelling, bombardment, etc. that helps the enemy adjust further shelling. But recently, cases of using social media for criminal, subversive activities have become more and more frequent. Ukrainian law enforcement officers share recorded cases of Russian curators recruiting perpetrators for crimes against Ukrainian defenders in Telegram. Sometimes it was possible to stop the crime, in other cases - we have facts of the death of Ukrainian servicemen and the perpetrators themselves. The objective of this study is to analyze similar cases (Telegram, law enforcement statements) to establish patterns and trends in such offenses and then to develop recommendations for systematic countermeasures and prevention of their occurrence in the future.

ABSTRACT. Disinformation is often framed as a foreign toxic substance, injected into public discourse by external adversaries, or as viral contagion spreading through digital networks. Such imaginaries, rooted in security concerns and biomedical metaphors, reinforce the idea that disinformation is a static thing—a form of informational pollution that can be traced back to identifiable origins and neutralized through countermeasures. This paper challenges this “reified” understanding by foregrounding disinformation’s processual, participatory, and translational dimensions. Rather than treating disinformation as fixed units of meaning, we examine how they mutate as they traverse digital ecologies, are adapted to different platform affordances, and are “translated” to the concerns of different publics through audience engagement.

We zoom in on contemporary Russian-Ukrainian themed disinformation narratives popular in the West (e.g. Biolab conspiracy theories & the Russian Doppelgänger operations) to analyze how they shift and evolve as they move across legacy and social media environments. Rather than a straightforward, linear dissemination process, this circulation involves active processes of translation and adaptation, in which audiences actively remix content. In some cases, these bottom-up meaning-making processes feed back into state-aligned propaganda and counter-disinformation efforts. This participatory feedback dimension complicates dominant scholarly understandings, showing how disinformation is as much a dynamic, localized, and bottom-up process as it is a state-driven strategic propaganda tool.

Methodologically, we employ a variety of computational and qualitative research methods to track, visualize and understand how these disinformation narratives morph into new constellations as they migrate across different platforms and audiences. By doing so, we also highlight disinformation as an ongoing negotiation of meaning in online and offline media environments. This paper argues that understanding disinformation requires a shift away from static, top-down, “hypodermic needle” disinformation models toward an approach that accounts for the multidirectional, participatory, and translational processes that shape its circulation.