Are Scientists Biased Against Women Scientists? Part I

Is science biased against girls and women? This is the first of a two-part series. In this first part, I describe why the answer to this question is not quite as simple as many people seem to assume.

There are many ways one might examine this question. One might look at the amount of science to which parents expose their boys and girls. One might examine how boys and girls are treated in high school or college. One might examine whether research on humans includes more men than women, or has hidden assumptions that male characteristics are normal.

This essay does none of that, and, therefore, does not address whether there is sex bias against girls or women in any of those ways. If you are interested in a short review of evidence bearing on the role of gender bias in producing the gender gap in Science, Technology, Engineering, and Math, this prior essay of mine would be a good start.

Instead, it examines a very specific thematic question: Are scientists biased in their evaluations of the work of men and women in science?

Unfortunately, “bias” can mean a great many things, none of which are quite the same. Sometimes, people use simply to refer to two groups that are unequal. Sometimes it means prejudice. Sometimes, it means discrimination. How these ideas, or claims, are related yet different is beyond the scope of this essay, which, instead, deals only with gender bias.

I use the term “gender bias” in this essay exclusively to refer to differences in evaluations of men versus women, all else being equal. So, for example, someone who believes that men are taller than women would not be “biased” unless they believed men who are 5’ 8” tall are taller than women who are 5’ 8” tall (or vice versa).

Easy, right? The research will provide a simple yes or no answer, right? No.

I realize “everyone knows” (or, at least, some think they know) that society is biased against women writ large, and they may be right. Certainly, historically, many societies, including but not restricted to the U.S. were biased against women. Until the early 20th century, women were not permitted to vote, and were effectively prohibited from entry to many professions. Once married, they were all-but-property of their husbands.

But this is the 21st century, not the early 20th. Women being unable to vote in 1900 provides no directly relevant information about whether society is biased against women now. Again, though, the question in this essay is not “is society biased against women,” but a much smaller piece of that very large question: Are scientists biased in their evaluations of the work of men and women in science?

Unfortunately, references to societal oppression of women 100 years ago, or 50 years ago, or of socialization practices in the present, or wolf-whistling by real or imagined construction workers even right now does not bear on this question. What does bear on this question? Evidence that assesses whether scientists evaluate male or female scientists more positively. Overall evaluations might be informative, but the gold standard will be evidence that evaluates whether scientists do so, for the exact same accomplishments. If men and women have different accomplishments, the issue becomes much stickier. Is it bias or is it the different accomplishments that drive evaluations (although some research can and has addressed this problem by addressing whether there is sex bias that is not explained by differences in accomplishments).

So far, we have three possible answers to the question:

1. Scientists are biased against women

2. Scientists are unbiased

3. Scientists are biased against men.

But it can get even trickier. Ingroup bias refers to the idea that people favor their own groups. Thus another possible answer is:

4. Ingroup bias: Women are biased in favor of women; men are biased in favor of men.

This can get even trickier, though, because one group may show ingroup bias but the other may not. Men may be biased in favor of men, but women may be unbiased; or the reverse may be true: women may be biased in favor or women, and men may be unbiased.

And, because I know much of this research literature quite well, it turns out that it is necessary to add a fifth category:

5. Research that reached the conclusion that there is bias against women scientists, but which has been subject to highly plausible doubts, re-analyses concluding otherwise, or outright refutation.

This latter category is important because it may contribute to exaggerated beliefs in the prevalence of sex biases in science. Often, when a study has some dramatic claim, but is subsequently debunked, the original, debunked study continues to be cited as evidence in support of the debunked claim. This is a well-known dysfunction in science and in science communication with the public.

In the rest of this essay, I give one detailed example that falls into each category, in order to give you a feel for what such research looks like; how it was conducted and what it found.

1. Scientists are Biased Against Women

Moss-Racusin et al (2012) performed a single study involving 127 academic scientists in biology, chemistry, and physics who evaluated a qualified but not overly excellent candidate for a lab manager position (scientists often hire lab managers to run the day-to-day operations of a lab – such as scheduling, record-keeping, purchasing, collecting data, etc.). Half the time, the candidate was named “John,” and the other half the time, “Jennifer.” Both male and female scientists rated John as more competent and more hirable than Jennifer.

2. Scientists are Unbiased

Forscher et al (2019) had over 400 scientists review actual grant proposals submitted to the National Institutes of Health. The names on the proposals were removed and replaced with names indicating either that the Principal Investigator (the main scientist submitting the proposal was either a White Male (e.g.,, Brad Sullivan), White Female (e.g., Anne Kelly), Black Male (e.g., Darnell Washington), or Black Female (e.g., Tanisha Robinson). They tested for bias literally in over 4000 different ways. No matter how they did it, they found no evidence of either sex or race bias.

3. Scientists are Biased Against Men

Another series of studies included 5 experiments and involved 873 tenure/tenure-track faculty participants in a wide variety of STEM disciplines (Williams & Ceci, 2015). They found that faculty displayed a 2:1 bias in favor of female applicants, except male economists who displayed no gender bias

4. Ingroup Bias

Veldkamp et al (2017, Study 4) asked scientists from many disciplines to evaluate men and women scientists. They found striking evidence of ingroup bias among women scientist respondents, who evaluated female scientists as more rational and open-minded, and higher in integrity, than they evaluated male scientists. Male scientists, in contrast, show no comparable pattern, and, instead, evaluated the male and female scientists’ objectivity, openness and integrity similarly. One limitation of this study is that, although it did assess scientists evaluations of male and female scientists, it did not directly assess their evaluations of articles or grant proposals.

5. Research that reached the conclusion that there is bias against women scientists, but which has been subject to highly plausible doubts, re-analyses concluding otherwise, or outright refutation.

Lee & Ellemers (2014) examined sex differences in grant funding rates among Dutch scientists. They found a slight tendency for male scientists to be funded at a higher rate than female scientists (17.7% vs. 14.9% funding rates). There were, however, two problems. First, the study did not even attempt to assess, or control for, application quality (this would be possible, e.g., by obtaining blind ratings of the actual proposals). Second, these bias results evaporated when Albers (2015) reanalyzed the data separately by field (health, physics, etc.). Put differently, Albers discovered that Lee & Ellemers bias evidence suffered from Simpson’s Paradox: a statistical pattern whereby something that is true for some large group need not be true for any subgroup. See this earlier essay for a detailed explanation of Simpson’s Paradox, and an easy-to-follow concrete example. In short, in Lee & Ellemers’ data, women were more likely than men to apply for grants in fields with lower funding rates, and this difference, rather than bias within fields, explained the overall sex difference in funding rates.

A few final points:

So which is it? Is science biased against women? Men? Neither? Both? Unfortunately, this essay cannot and did not answer that question. It merely shows the breadth of evidence one must consider if one wishes to answer that question. In my experience, precious few people even attempt to consider the full breadth of the evidence.

I presented one example of each type of result mainly to give you, gentle reader, a sense of how such research is conducted and what has been found under each type of finding. You would not be justified in concluding “all five patterns are equally likely to occur” just because I only presented one example of each. This was not a comprehensive review of the evidence of gender bias in science.

My next essay in this two-part series provides a far more extensive list of empirical studies under each of the five headings.

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I realize gender bias can be controversial. I would be delighted for you to post a comment, but, before doing so, please read my Guidelines for Engaging in Controversial Discourse. Short version: Keep it civil (no insults or ad hominem, no profanity or sarcasm), brief, and on topic, otherwise I will take your comment down.

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If you find this essay interesting, feel free to follow me on Twitter, where I routinely discuss this sort of thing. Unfortunately, on Twitter, I cannot take down the comments of those who are uncivil, so, sometimes, things get a little testy. Feel free to disagree, even strongly, but here I can and will enforce civil exchange of ideas.