Damegender: Towards an International and Free Dataset about Name, Gender and Frequency

EasyChair Preprint 5763, version 1

Abstract

  Equality of gender is the 5th objective of sustanaible development
  in United Nations

  This equality can be reached working on measure and analyze data and
  to apply politics from the results. On many gender studies, we need
  to count males and females deciding gender from names, for instance,
  research papers, job positions, streets, ... The traditional way is
  to use commercial APIs with propietary data without idea about how
  the data has been built. Another way, is taking data from wikipedia
  or scientific sites.

  With Open Data idea, many statistics institutions are providing Open
  Datasets about name, gender and frequency. So, we need a scientific
  discussion about unifying formats, make easy ways to process these
  data and ways towards make standards. In this discussion, we take
  into account minorities, for example, LGTB claims such as attending
  the non binary reality.

  The dataset is covering more than 20 countries in the occidental
  world. Having more names than any open source software in this
  moment. Allowing to measure gender gap to students and academics
  interested on the phenomenon.

  There are a warranty of quality on reproducible research the
  citation about official sources provided by statistics institutions
  making easy the peer review and opening doors to the semantic web
  and the attention to minorities such as trans gender people, or
  cultures with own languages in states with another main language
  doing more cheaper to measure the gender gap.

Keyphrases: Gender Detection Tool from the Name, gender gap, open datasets

@booklet{EasyChair:5763,
  author    = {David Arroyo Menéndez},
  title     = {Damegender: Towards an International and Free Dataset about Name, Gender and Frequency},
  howpublished = {EasyChair Preprint 5763},
  year      = {EasyChair, 2021}}