{"id":1113,"date":"2020-08-24T06:19:58","date_gmt":"2020-08-24T10:19:58","guid":{"rendered":"https:\/\/drsmith.blog.yorku.ca\/?p=1113"},"modified":"2022-09-29T12:16:15","modified_gmt":"2022-09-29T16:16:15","slug":"gendered-language-in-job-ads","status":"publish","type":"post","link":"https:\/\/www.yorku.ca\/professor\/drsmith\/2020\/08\/24\/gendered-language-in-job-ads\/","title":{"rendered":"Gendered language in Job Ads"},"content":{"rendered":"

[updated 2021 & 2022]<\/em><\/p>\n

We don't hire enough women in Engineering and Computer Science faculties. \u00a0It's a peer-reviewed fact<\/a>.<\/p>\n

And, yet, hiring committees continue to refuse to use the same rigour and critical thinking in finding a new colleague that they demand in their every-day research. \u00a0Where's the evidence<\/em> that your ad-hoc, \"mmmm.... feels good<\/em>\" job ad works?<\/p>\n

Best practice, workable solutions for dealing with this exist, and they've been examined by a multitude of people, including within the Canadian<\/a> context<\/a> (WWest summary on hiring committees<\/a>; archive<\/a>). \u00a0An in-depth examination can be found in Iris Bohnet's book<\/a>, \"What Works\" (my review<\/a>, video recap of research by Dr. Bohnet<\/a>)\u00a0 One of my take-aways from the book is that we must get to a minimum 30% ratio as quickly as possible to make progressive and long-lasting change.<\/p>\n

Each hiring exercise we go through in our faculty is an opportunity to get closer to that 30%. \u00a0\u00a0The first thing to do is to focus the job ad: the words and the venues. \u00a0Here, I'm focusing on the first part.<\/p>\n

The words we use in the job ad matter (video<\/a>), just like they matter when companies like Coca Cola make the billion dollar decisions to attract more clients by changing the name of their products (\"Diet\" Coke to Coke \"Zero\").\u00a0 Academic job ads are not immune to this. Take a look at most of them and they use words like \"decisive\", \"independent\", \"active\", \"strong.\" \u00a0These are gendered words (WWest PDF<\/a>; archive<\/a>). They're keyed for men to respond positively to. \u00a0They have a negative outcome on women applying for jobs.<\/p>\n

In 2017 I brought up these issues as we debated, yet again, what to do about \"women not applying for professor jobs\" in our engineering and computer science department. \u00a0I suggested that we reword the job ad and to use professional tools<\/strong> and evidence-based best practices<\/strong> to do so. \u00a0Why? \u00a0Because rewording it will not significantly reduce the number of men applying. \u00a0Stastically-speaking, men don't care what the job requirements or wording is. \u00a0They'll still apply. \u00a0However, the effect of the wording on women is profound. \u00a0Male-gendered wording is known<\/a> to reduce the number of female applicants. \u00a0So,\u00a0coding your job ad with female-gendered words will have no significant downside.<\/strong>\u00a0 With that in mind, I used two automated word analysis tools to do most of the heavy-lifting in the rewrite:<\/p>\n

    \n
  1. Free & Simple Gendered word decoder:\u00a0http:\/\/gender-decoder.katmatfield.com\/<\/a><\/li>\n
  2. The more capable \"wizard\"\u00a0https:\/\/textio.com\/ <\/a><\/li>\n<\/ol>\n

    Textio no longer runs the free trial<\/em> I used but Kat Matfield's site<\/a> is still up. (Journal article<\/a> by Gaucher, Friesen and Kay) It looks up words in your job ad to see if they're known<\/a> to be male gendered. \u00a0 Here is a comparison between the old version and the new version:<\/p>\n