Examining potential mechanisms underlying the Wikipedia gender gap through a collaborative editing task

Gender stereotypes embedded in natural language are stronger in more economically developed and individualistic countries

Gender stereotypes contribute to gender imbalances, and analyzing their variations across countries is important for understanding and mitigating gender inequalities. However, measuring stereotypes is difficult, particularly in a cross-cultural context. Word embeddings are a recent useful tool in natural language processing permitting to measure the collective gender stereotypes embedded in a society. In this work, we used word embedding models pre-trained on large text corpora from more than 70 different countries to examine how gender stereotypes vary across countries. We considered stereotypes associating men with career and women with family as well as those associating men with math or science and women with arts or liberal arts. Relying on two different sources (Wikipedia and Common Crawl), we found that these gender stereotypes are all significantly more pronounced in the text corpora of more economically developed and more individualistic countries. Our analysis suggests that more economically developed countries, while being more gender equal along several dimensions, also have stronger gender stereotypes. Public policy aiming at mitigating gender imbalances in these countries should take this feature into account. Besides, our analysis sheds light on the "gender equality paradox," i.e. on the fact that gender imbalances in a large number of domains are paradoxically stronger in more developed/gender equal/individualistic countries.

Exploring the gender gap in the Spanish Wikipedia: Differences in engagement and editing practices

Wikipedia's significant gender bias is widely acknowledged. In this paper we analyze the Spanish Wikipedia with the aim of estimating the percentage of women editors and measuring their engagement and editing practices with respect to their men counterparts. To identify the gender of Wikipedia registered users, we analyzed both the information contained in their user profile and the information provided by users about themselves on their personal user pages. Using our own coding procedure, it is possible to identify a greater number of women than by relying only on the gender reported in their user profile. Combining both methods, our results show that the percentage of women is small, a meagre 11.6% of all analyzed editors, though there is still a significant percentage of users whose gender cannot be determined by either method. Men outnumber women in all Wikipedia namespaces in a ratio that is always equal to or greater than 3:1. This fact can be partially explained by the lesser persistence of women editors, who tend to leave Wikipedia much more quickly. There is, however, a small group of veteran women editors who, in some cases, surpass men editors in terms of their editing practices and participation in different Wikipedia namespaces.

Evolution of Wikipedia's medical content: past, present and future

As one of the most commonly read online sources of medical information, Wikipedia is an influential public health platform. Its medical content, community, collaborations and challenges have been evolving since its creation in 2001, and engagement by the medical community is vital for ensuring its accuracy and completeness. Both the encyclopaedia’s internal metrics as well as external assessments of its quality indicate that its articles are highly variable, but improving. Although content can be edited by anyone, medical articles are primarily written by a core group of medical professionals. Diverse collaborative ventures have enhanced medical article quality and reach, and opportunities for partnerships are more available than ever. Nevertheless, Wikipedia’s medical content and community still face significant challenges, and a socioecological model is used to structure specific recommendations. We propose that the medical community should prioritise the accuracy of biomedical information in the world’s most consulted encyclopaedia.