The Gender Gap Grader toolkit is a set of open source and open APIs to support the gender data revolution. We would like to make it possible for ANYONE to run their own gender gap study, where it matters to THEM.
Currently, most companies and organizations produce aggregated statistics, which often masks more subtle differences. We make it possible to use any database with personal names (for example, a company organizational chart, a company wide LDAP directory with roles and resposibilities, etc.) to produce new disaggregated gender data that can be analyzed from all angles.
The Gender Gap Grader toolkit uses the API made by NamSor, the market leader in global name-to-gender classification, which covers not just the United-States but all regions of the World, alphabets and languages. It is free to use to classify up to 5000 names. The simplest way to append data to Google Sheets or Excel Sheets is to export your data to a CSV file (CSV UTF-8 for international names in non-LATIN alphabets) and then run it using the online CSV Tool.
Here are some prominent research using or citing NamSor Gender API,
- The Gender Gap in Computer Science—A Bibliometric Analysis FAU
- Comparison and benchmark of name-to-gender inference services PeerJ Computer Science
- Gendered geography: an analysis of authors in The Lancet Global Health Elsevier
- A Bibliometric Approach for Detecting the Gender Gap in Computer Science COMMUNICATIONS OF THE ACM
- Elsevier Gender 2020 report – The Researcher Journey Through a Gender Lens Elsevier
- Gender, Law Enforcement, and Access to Justice: Evidence from All-Women Police Stations in India American Political Science Review, 2020
- Gender and Innovation EBRD
- Gender and racial/ethnic disparities in academic oncology leadership. Journal of Clinical Oncology
- Gender differences among active reviewers- an investigation based on Publons
- Subject Coverage, Gender and Race in Carolina Digital Repository Content
- How diverse is the ACII community? Analysing gender, geographical and business diversity of Affective Computing research
- Retraction according to gender: A descriptive study ACCOUNTABILITY IN RESEARCH, 2021
- Performance of gender detection tools: a comparative study of name-to-gender inference services
- Meta gender study: A Gender Study of Global Distribution on Gender Studies
- Google Summer of Code Gender Diversity
- On the Value of Encouraging Gender Tolerance and Inclusiveness in Software Engineering Communities “Information and Software Technology Volume 139, November 2021, 106667”
- Gender Classifier Evaluation Report