Gender bias in open source : Pull request acceptance of women versus men
▻https://peerj.com/preprints/1733
Gender bias in open source : Pull request acceptance of women versus men
▻https://peerj.com/preprints/1733
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.
Donc quand une femme propose du code, il est plus souvent reconnu comme du bon code que celui des mecs.
Mais si on sait que c’est une femme, elle se fait virer plus souvent.
Pour le deuxième point, on le savait (mais là ça fait une étude chiffrée en plus…). Mais le premier point est intéressant du coup !
cc @touti @aude_v
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