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Lee, could you write a post on the same audit studies of black-white differences in callbacks. From what I understand, almost every study shows a significant difference in callbacks where black applicants receive fewer callbacks than white applicants. I would just appreciate your perspective on those studies and their methodology.

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Sorry, missed this comment when you made it. Generally, audit studies are high quality. In my queue is a sketch on just this.

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It is good to hear that hiring practices have become more equal. I feel like "work place discrimination" encompasses much more than just callbacks though.

Other studies I have seen have also discussed how men tend to be rewarded for aggressive or even sociopathic behavior but women are punished for the same behavior, resulting in lower evaluations and lesser compensation for the same work.

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Jan 25Liked by Lee Jussim

This is excellent, I shared it on Twitter. I hope it is widely cited and used

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Thanks for that.

I'll add that from my perspective working on the law/philosophy of discrimination, it too often seems to be the case that researchers use very vague and unclear notions of discrimination and bias, some that are ambiguous between different possible interpretations (some of which appear morally objectionable but others aren't, and some may be objectionable only in certain circumstances or under particular conditions), and often unnoticeably switch these different notions mid-study - for instance, describing one form of discrimination/bias in the intro or motivation, then with the actual operationalization part, they'll use parameters that would be adequate for measuring another type of discrimination.

For instance, "bias" is often ambiguous between: (1) something like negative attitudes or degrading stereotypes directed at a certain group of people, and (2) something like decisions that would lead to unfair outcomes according to some appropriate standard. Many studies about discrimination/bias in policing, for instance, conflate the two (throughout one study), and make unfounded implicit assumptions about the connection between them (for instance, that (1) necessarily leads to (2), or leads to (2) across a variety of circumstances significant for the study's purposes, etc., while this isn't necessarily the case).

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I am not sure if the group's analysis would have captured something that I have seen commonly over the past 30 years both as a job candidate and later search committee member in a STEM field. Many if not most announcements for jobs have gone out of their way to stress in various wordings that women and minorities are particular encouraged to apply. To me this sends the message that these groups are PREFERRED applicants over those who are NOT in the preferred category. I have seen searches where it is the official policy goal to hire a woman or a person of color. When the administrator making the final hiring decision and responsible for the tenure and promotion of all members of the search committee makes such a statement I would say that is clearly placing a discriminatory influence on the hiring process. In one such search, the white male candidate from within the institution was told he was welcome to apply but should not expect to be hired if the most remotely qualified woman applied. In another search, a member of the search committee vowed that he would never recommend hiring a white male because too many such have been hired in the past. While I have seen many such actions which make clear a bias in favor of women and/or people of color, I have yet to find a single instance where the bias worked against those demographic groups. Given that men who complain about discrimination by women are not taken seriously by HR offices almost exclusively run by women and minorities, one might expect that a lot of discrimination may not be found in the studies in question.

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As someone who has been hiring and firing for more than three decades, I’ve found that people who do well academically are easy hires; women outclass men academically - graduation rates have shifted - which I believe drives a lot of this shift.

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When you say that the women outclass the men academically, I have to wonder what measure you are making to come to that conclusion. Can you provide some insights?

In my career in STEM I have seen a lot of women with very thick resumes which shrink rapidly when you remove all the award and opportunities they tout which are reserved to women and not available to their male competitors for the job. Are women actually better...or are they being afforded more gender biased opportunities to LOOK like they are better than they really are? As we have seen with the arrival of Trans Athletes in Women's sports, on an actual LEVEL playing field, athletically, the best women in the world in most sports come in behind hundreds of men.

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Girls and women do better at every level of school, from first grade through college. Higher grades, higher graduation rates, etc. In fact, brilliant h.s. girls tend to be broadly brilliant, whereas brilliant h.s. boys tend to be brilliant at math and science. But this difference probably explains some of the STEM gap (brilliant girls have more career options than brilliant boys, so fewer end up in STEM; brilliant boys are less likely to have such broad options):

https://www.psychologytoday.com/us/blog/rabble-rouser/201707/why-brilliant-girls-tend-favor-non-stem-careers

BUT, none of that can readily explain the audit study meta-analysis described here. Why not? Because the whole point of an audit study is to *hold applicants' records/resumes/experiences constant*! Thus, whatever academic differences may exist are irrelevant to the results of the audit studies, because, experimentally, they rendered them identical in those studies.

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Oh dear. Lee, I love that you dare to ask the important questions, but please be warned about what will happen to you and your co-authors. The truth you have revealed about workplace sex discrimination would surprise few normal people not in the pinnacles of power or far from the sway of the Ministry (Herstory) of Propaganda otherwise known as Women's Studies. You have, however now stood in a puddle while grappling the third rail. You have dared to challenge one of the Big Feminist lies on which the Misogynistic Women's movement relies on to justify their bullying and blatantly inequitable and diversity killing demands for special rights and power. You might as well have responded to demands of the #MeToo Movement to "Believe the Woman!" by asking, "Why?" while pointing at the data on convictions versus false accusations from law enforcement sources. You do realize that failing to find evidence to support the feminist narrative will be seen as a evidence that you are pursuing a misogynistic agenda on behalf of the patriarchy. You and your co-authors will likely experience the following over the next few months:

1. Shrill complaints attacking your results with various attacks on your techniques or failure to show due deference to the "literature" which is code word for studies which show the appropriate outcome regardless of their actual validity.

2. Your intentions will be questioned, usually by suggesting version of a desire to exploit the suffering of women for your own professional gain or a naivete that your actions will undermine women's voices and enable others to question the suffering they experience in the workplace.

3. Your funding sources will be questioned and even may receive complaints about funding your "dangerous" or "dishonest" work.

4. You may find conference presentations and invitations to be suddenly absent or rescinded. Abstracts may actually be rejected before the conference itself.

5. Potential colleagues/collaborators working with you will be contacted and bullied about not facilitating your conduct.

6. You may even find yourself facing Code of Conduct violation accusations for the impact of your dangerous work which creates a hostile environment for women in the workplace.

I would love to be able to say predictions 1 to 6 won't prove to be correct...but experience speaks loudly. Thanks for this work. Please do share the link to the paper when it comes out!

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Jan 25Liked by Lee Jussim

I would have hypothesized that academics make worse predictions than the general public as they 1) are more removed from the business of typical workplaces and 2) are more ideologically homogeneous. So I'm pleasantly surprised with that result, tbh. I wonder how it would look with academic jobs. Would there be bias? Would academics be more accurate?

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Jan 25Liked by Lee Jussim

Below is a recent Adversarial Collaboration that looked at gender discrimination in academic science. The authors analysed literature on bias published between 2000 and 2020.

They focused on 6 key areas: tenure-track hiring, grant funding, teaching ratings, journal acceptances, salaries, and recommendation letters.

There was no difference between men and women in 3 of the 6 areas and women were advantaged in 1 of them: hiring. For teaching ratings and salary, there was evidence of bias against women but for salary it was lower than often claimed.

https://doi.org/10.1177/15291006231163179

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