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Du code et des loutres

    • This paper presents the largest study to date on gender bias, where we compare acceptance rates of contributions from men versus women in an open source software community. Surprisingly, our results show that women’s contributions tend to be accepted more often than men’s. However, when a woman’s gender is identifiable, they are rejected more often. Our results suggest that although women on GitHub may be more competent overall, bias against them exists nonetheless.

      #sexisme #logiciels_libres #informatique #github #femmes

    • Lu en diagonal, l’étude se heurte à la difficulté de ne pas faire d’étude in situ avec des interviews et n’analyse que des données, comme par exemple sur github savoir quel #genre est vraiment déclaré.

      Ce qu’il en ressort dans tous les cas est que les décideurs finaux sont des hommes. Donc, soit il faut se battre soit il faut se battre, et c’est fatiguant ce mur construit de préjugés sexistes tenaces qui explique le pourquoi du désengagement des femmes, la vie est courte.

      The most obvious illustration is the underrepresentation of women in open source; in a 2013 survey of the more than 2000 open source developers who indicated a gender, only 11.2% were women (1). In Vasilescu and colleagues’ study of Stack Overflow, a question and answer community for programmers, they found “a relatively ’unhealthy’ community where women disengage sooner, although their activity levels are comparable to men’s” (2).
      These studies are especially troubling in light of recent research which suggests that diverse software development teams are more productive than homogeneous teams (3).

      Yet another explanation is that women are held
      to higher performance standards than men, an explanation supported by Gorman and Kmec’s analysis of the general workforce (23)

      1/ L. Arjona-Reina, G. Robles, S. Dueas, The floss2013 free/libre/open source survey (2014).
      3/ B. Vasilescu, et al., CHI Conference on Human Factors in Computing Systems, CHI (ACM, 2015), pp. 3789–3798
      23/ E. H. Gorman, J. A. Kmec, Gender & Society 21, 828 (2007).

      #data_gender #genre
      Et merci pour le signalement @rastapopoulos