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

EasyChair Preprint no. 5763, version 3

Versions: 1234567history
5 pagesDate: September 26, 2021


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

  This equality can be reached working on to measure and to 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, making easy ways to process these
  data and ways towards make standards.

  The dataset is covering more than 20 countries in the occidental
  world, with more names than any open source software in this
  moment. Allowing to measure gender gap to students and academics
  interested on the phenomenon without costs and on a reproducible
  way, more people will be contributing to fix the gender gap.

  There are a warranty of quality on reproducible research, that's the
  Free Software and the citation about official sources about names,
  gender and frequency provided by statistics institutions making easy
  the peer review and opening doors to the semantic web and the
  attention to diversity.

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

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {David Arroyo Menéndez},
  title = {Damegender: Towards an International and Free Dataset about Name, Gender and Frequency},
  howpublished = {EasyChair Preprint no. 5763},

  year = {EasyChair, 2021}}
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