Gscan
Gscan is a AI-based software tool that detects words and expressions used in a job advert, which are specific for a gender and then converts them into a gender neutral form. This enables you to make job ads equally attractive to women and men, and recruit from the entire talent pool available. By using Gscan, you will recruit more talented candidates, get a gender diverse candidate pool and save time on your recruitment. Furthermore, Gscan provides you with a score that informs you about the degree of gender neutralization of your ad, that you can then benchmark across your industry.
What is the Science behind Gscan?
Scientific studies have proven that we use specific gender words and expressions when writing job ads, which makes these job ads biased toward a specific gender and discourages one half of the talent pool from applying. This type of bias is implicit and unconscious because it has been naturally embedded in our written and spoken language, and thus almost undetectable. Therefore, technologies are required to help us detecting it, and thus eliminating it for making our job ads attractive to the entire candidate pool. At Develop Diverse, we use state-of-the-art methods in Natural Language Processing and Machine Learning to detect and neutralize biased words and expressions used in the text.
Do you have an implicit bias? - Take the Harvard test and find out!
If you don’t know what implicit bias is, or you don’t know if you have it; we invite you to check it out in the implicit bias test done by Harvard University: https://implicit.harvard.edu/implicit/takeatest.html
Scientific Articles And Reports
Hunt, V., Layton, D., and Prince, S. Diversity Matters. McKinsey & Company, 2015
Freeman, RB., and Huang, W. Collaborating with People Like Me: Ethnic Coauthorship within the US, Journal of Labor Economics, 2014
Catalyst, 2011
Burt, RS. Structural Holes and Good Ideas. American Journal of Sociology, 2004
Waither, is that inclusion in my soup? Research report 2013, Deloitte Australia
Gaucher, D., Friesen, J., & Kay, A. C. Evidence That Gendered Wording in Job Advertisements Exists and Sustains Gender Inequality. Journal of Personality and Social. Psychology, 2011
Newman, ML., Groom, CJ., Handelman, LD., and Pennebaker, JW. Gender differences in language use: an analysis of 14.000 text samples. Discourse Processes, 2008
