Does language on a resume/CV interfere with gender blind recruiting? Find out what we discovered as well as the power of language when it comes to job descriptions and diversity hiring.
From the very beginning of the candidate hunt, you could already be limiting your applicants. Moreover, the way you write your job descriptions is already limiting which gender will be the majority of your applicants. A study by The Journal of Personality and Social Psychology found the gendered wording in job descriptions affected who would apply for those positions. They found women were more interested in men dominated positions when the advertisements were unbiased and did not refer to the applicant as He. But, still today, there are issues with the way we write job descriptions and titles. Here’s how this can be solved:
1. Write job descriptions in a gender-neutral tone.
When referring to the position, only use the official title of the position or use “they.” Also, avoid including words in your titles like “hacker,” “rockstar” or “ninja.” It’s a turn-off for women and you’re likely to get less female applicants.
2. Avoid superlatives.
Excessive use of words like “expert” and “world class” will result in women looking the other way because women generally are more collaborative than competitive.
3. Limit requirements.
Identify which requirements are nice to have versus must-have and remove the nice to have requirements from the job description. Research shows a woman will typically apply if they meet 100% of the requirements. Men will usually apply if they meet just 60% of listed requirements.@Oleeo_ partnered with University College London and conducted the first large-scale statistical #linguistic analysis of male and female CVs/resumes across multiple industries. Learn what they found:Tweet This!
At Oleeo, we focus a lot on Machine Learning and Intelligent Automation. We use algorithms to select great candidates. So, we wanted to know if these differences we see in job descriptions also exist in CVs/resumes, and, do they perpetuate biases unconsciously through recruiters? We partnered with University College London and conducted the first large-scale statistical linguistic analysis of male and female CVs/resumes across multiple industries and looked at 200,000 applications and CVs/resumes from the U.S. and UK.
Our first objective was to establish features that may differentiate a male resume from a female resume. We looked at the lexical, syntactic and semantic differences in the text. Then, we wanted to know if these differences are perpetuated or amplified in machine learning. We found, for the industries we focused on, there were 10 words found for each gender that the discriminant word analysis identified. The results were remarkable.
In each industry, we found women used “soft” words. 90% of the top 10 male discriminant words are proper nouns and nouns compared to 68% of the top 10 female discriminant words. Beyond nouns, we found that patterns easily lead to gender identification. We also found female CVs/resumes tend to be longer, use more unique words and have a higher readability. You may not realize it, but your brain probably knows if you’re reading a male or female resume. These results we found were so significant and solidify the fact that it’s time to reset and remove bias from your process.
Using algorithms and intelligent automation, we can finally level the playing field with the program’s ability to pick out top candidates. Doing so can and will you get you the best candidate in the right position. So many women were looked over for a position in an orchestra that would have made wonderful additions to the group. Subconscious biases happen. Once you recognize the bias, you can get around it. Whether it’s a screen, a celebrity judge with their back to a singer or Intelligent Automation - you can overcome biases with Oleeo’s Intelligent Automation.
Download the full diversity hiring eBook as a guide to gender blind recruiting and overcoming bias here!