totaljobs Gender Bias Decoder
Research from the University of Waterloo and Duke University has defined a group of words that carry a gender weighting. They include words that have been given their gender weight through historical, cultural and social use. Broadly, we have come to associate certain words with certain genres.
The aim of the tool and the accompanying study was to enable employers to improve their diversity and allow them to receive a better balance of applicants.
Total Jobs approached us to create an accessible online tool that allowed users to analyse passages of text, specifically job adverts for gender bias.
Th Gender Bias Decoder was created using a database of words from a research paper written by Danielle Gaucher, Justin Friesen, and Aaron C. Kay: Evidence That Gendered Wording in Job Advertisements Exists and Sustains Gender Inequality(Journal of Personality and Social Psychology, July 2011, Vol 101(1), p109-28).
The design of the tool was kept simple and inline with existing total jobs branding. It was deemed important that a visitor to the site would feel they were still within the total jobs ecosystem. The data is stored in a CSV file which can be updated by the client. The contents of the CSV populates the list of words on the homepage as well as providing the look up for the tool.
As well as receiving coverage from publications such as Cosmopolitan, total jobs also used the Gender Bias Decoder to analyse 70,000 job ads that had been uploaded to their own site.
They found that only 13% of adverts uploaded were gender neutral. This sort of data makes it really clear that employers are not paying enough attention to how they are recruiting job seekers, unconsciously skewing their potential pool of applicants and in all likelihood, putting off talent from applying.
Read more about it on the total jobs site.