Potential Job Application Gender Gap Revealed in Early Research Findings from Univ. of Pittsburgh Study

This article was contributed by a research team from the University of Pittsburgh, and represents their take on the initial findings of a research study on potential job application gender gaps and bias.

When it comes to making sure the right candidate finds the right job, it’s the responsibility of every organization and hiring team to ensure everyone with the right skills gets equal access to opportunities.

Although many employers are making strides when it comes to improving diversity in the workplace, there is still a long way to go.

One way that we can better overcome challenges that may prevent diversity in the workplace is by gaining a better understanding of the specific factors and biases that may be unintentionally limiting diversity. At this point in time, there are a number of reasons why gender differences in the workplace may exist for certain roles. To explore one facet of this massive topic, Phenom recently began collaborating with researchers at the University of Pittsburgh* to explore job descriptions as a possible factor that may affect lack of diversity in male-dominated occupations. Knowing the reasons for gender differences in application rates is one small, but important step toward understanding how to increase diversity.

Here are their initial findings and recommended considerations for employers to reduce bias in job descriptions.

A Job Application Gender Gap: Women Consider Male-Dominated Occupations, But Apply Less Frequently Than Men

Authors: Dor Morag, David Huffman, PhD and Alistair Wilson, PhD
Department of Economics, University of Pittsburgh

As economists, we wanted to understand how people make decisions as they think about applying for a job. We were particularly interested in understanding how these decisions vary for men and women. Recent academic papers have probed the differences between men and women in how they react to job offers.

For example, by surveying college student seniors over multiple years, economists have found that, on average, women are willing to give up 7.3% of their salary (compared to 1.1% for men) to have more flexible work arrangements, and are willing to give up 4% for better job security (compared to 0.6% for men). These findings have focused on differences at the job offer stage, and can matter greatly for companies aiming to hire more women. But we set out to look at whether or not there are major differences in how men and women search for jobs and consider whether or not to apply to the jobs they view.

There are a few reasons why there might be gender differences in application rates for certain types of occupations, which contribute to particular occupations being predominantly filled by men:

One possibility is that many women do not consider jobs in these male-dominated occupations.
Another possibility is that women are considering applying to these positions, but are ultimately discouraged by something in the job description.

Up until this point, there has not been much evidence regarding gender differences in job searches and applications — mostly due to economists lacking data on the jobs people apply to, let alone data on the jobs they did consider but ultimately did not apply to. This is an area we wanted to explore further. Because of Phenom’s unique position in the job search and application process, they provided us with hard-to-find data on job description views that gave us an initial window into this question.

Our key initial finding (represented in the figure below across all professions) is that when it comes to job postings in male-dominated professions, the rate of women applying to those jobs is lower than the rate of women considering the jobs.

Notes: The blue and purple curves show the conversion rates of views to applications for men and women separately. While the men's ratio is relatively stable at 50% (they apply to one out of two jobs they view), the women's ratio is lower for male-dominated occupations and similar to men's for female-dominated occupations. In yellow and orange are the share of women out of the viewers and the applicants. Both rise with the percentage of women in the workforce, as expected. But more importantly, the gap between them illustrates the implications of the different conversion rates. If women were applying to viewed jobs at the same level as men, their representation in the candidate pool of male-dominated occupations would have risen by about 10%.

We found that women look at these job descriptions at higher rates than their representation within these professions, but far fewer women are applying. While the figure shows the effect across all professions, we can jump into particular occupations to make this concrete.

For example, the share of women in the labor force for maintenance and repair workers is 5% nationally (BLS, 2022). In the Phenom data, job descriptions for this occupation had 304 male and 57 female viewers, which means women represented 16% of those viewing the postings. Out of these viewers, there were applications from 157 men (52% yield from the viewers) and only 11 women (a 19% yield) — making women’s share in the applicant pool less than 7%.

A similar story is present for mechanical engineers with 8% women in the workforce, where 39% of female viewers applied for such jobs, compared to 54% of the male viewers.

In contrast, there is no gap when we look at occupations where women already have greater representation. As an example, consider customer service representatives, where women comprise 65% of the workforce. Here women and men exhibit similar conversion rates, where 53% of the female viewers ultimately applied, and 54% of the male viewers.

What do these findings mean for HR professionals?

An immediate implication is that it’s worth thinking hard about the substance of the job descriptions in male-dominated occupations (e.g., certain engineering positions, drivers, mechanics, constructors) that may deter applications from women who are considering these jobs. Below, we suggest a couple of possible explanations for the conversion-rate gender gap in male-dominated professions. Each one implies different strategies for diversifying the applicant pool and may be more or less relevant given the specific circumstances.

There is something in the content of job descriptions in male-dominated occupations that discourages women from applying. For example, the description might indicate that work hours are relatively inflexible or that job security is low due to a competitive environment, factors that women may care about more than men. If these are, in fact, components of the job, then increasing diversity may require changing these aspects.
The language in job descriptions matters. Psychologists have found evidence in laboratory studies that women report being less interested in applying to a job described with stereotypically masculine words (e.g., “competitive”, “force”, and “independent”). Could the greater prevalence of these words in job descriptions for male-dominated occupations also explain why less women are applying to these jobs as well? Relatively subtle word choices and phrasing could suggest that job security or flexibility are lacking, even if that’s not the case. If job language, rather than substantive employment conditions, is a source of the gender gap, then simple remedies are possible. Re-writing job descriptions, potentially using AI language tools, could improve the diversity of the applicant pool.

Our future research aims to provide clear data-driven answers to the question of what drives the gender gap in converting views to applications. We will test whether job descriptions in male-dominated occupations are more likely to have certain job characteristics — like lack of flexibility in work hours or job insecurity — that may discourage women from applying more so than men. We will also use natural language processing (NLP) tools to measure how different language appears in job descriptions across male-and female-dominated occupations and test for patterns that may explain gender differences in application decisions.

Watch this space for future updates!