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For International Women’s Day, you will find an interesting illustration of how NamSor can be used to produced an analysis of the gender gap in a particular field, using open data bases. In this case, the analysis shows a strong balance towards male authors in the University’s bibliographic materials recommended to students.
In the following example we have used the functionality of analyzing the gender of the names to quantify the extent to which the authors would be represented in the records marked in the catalog as recommended bibliography of the curricula of Philology and Communication (courses 2020-21 and 2021-22), extracting the probable gender from the names.
Limitations of the study:
Apart from the limitations of the application with possible gender assignment errors that we have not been able to detect (it must be said that the Namsor application cannot distinguish non-binary gender authors), with respect to the data set analyzed, this it only represents the recommended bibliography that is marked following the current agreed regulations (in general it is recommended that it does not exceed 10 titles for each subject). The list also does not cover all authors in the case of works with multiple authorship and authors with an unidentified initial name or works without a personal author are not taken into account.
The result according to the analysis of 2,638 bibliographic records is as follows: 21% of names would be classified as female (550) and 79% as male (2,088).
Also, this week was published the European Commission’s paper on gender diversity in Artificial Intelligence (AI),
DivinAI is an open and collaborative initiative promoted by HUMAINT in collaboration with Universitat Pompeu Fabra to measure and monitor diversity indicators related to AI conferences, with special focus on gender balance, geographical representation, and presence of academia vs companies. This paper summarizes the main achievements and lessons learnt during the first year of life of the DivinAI project, and proposes a set of recommendations for its further development and maintenance by the AI community.
NamSor™ Applied Onomastics is a European vendor of sociolinguistics software (NamSor sorts names). NamSor mission is to help understand international flows of money, ideas and people. We proudly support Gender Gap Grader.
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