Bias, Bias Everywhere

Admitting that scientists demonstrate gender bias shouldn’t make us forget that other kinds of bias exist, or that people other than scientists exhibit them. In a couple of papers (one, two), Katherine Milkman, Modupe Akinola, and Dolly Chugh have investigated how faculty members responded to email requests from prospective students asking for a meeting. The names of the students were randomly shuffled, and chosen to give some implication that the students were male or female, and also whether they were Caucasian, Black, Hispanic, Indian, or Chinese.

And the inquiries most likely to receive positive responses were the ones that came from … white males! You should pause a minute to collect yourself after hearing this shocking news. Here are the fractions of students who didn’t even get a response to their emails, and the fractions who were turned down for a meeting. (Biases aside, can you believe that over half of the prospective students who asked for a meeting were turned down?)

The results pretty much speak for themselves, and help to highlight the kinds of invisible biases that are impossible to detect directly but can end up exerting a large influence on the course of a person’s career. As previously noted, the first step to eradicating (or at least lessening) these kinds of distortions is to recognize that they exist. (Although a quick perusal of our comment sections should suffice to convince skeptics that the biases are very real, and oftentimes proudly defended.)

Interestingly, the studies didn’t only look at scientists, but at academics from a broad variety of disciplines, with dramatically different results.

It’s clear that scientists, while biased, are not the worst offenders here; that ignominious distinction belongs to faculty in business, education, and human services. Social scientists and humanities professors weren’t that biased at all, and faculty in the fine arts were significantly reversed-biased! Stereotypes are still stereotypes, even when they work in unusual directions — I maintain that white guys can still have artistic souls, despite the unconscious prejudices lurking within academia.

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40 Responses to Bias, Bias Everywhere

  1. Mr. Anthony says:

    There’s a banal explanation: Avoiding language barriers.

    But yah, the Hispanic female thing… sketchy!!!

  2. Curious George says:

    Very curious: How would

    caucasian females
    ignoring emails
    from any females

    influence this “statistics”?

  3. J. Rich says:

    @13 Why would someone who has “drunk party pictures” on facebook be somehow a less qualified candidate for an academic job? Unless the “drunk party pictures” were taken while they were operating an experiment or something, I’m not sure how that has anything to do with their professional qualities.

  4. James Gallagher says:

    I almost believe that Sean could pull up stats about people tripping on sidewalks/pavements and SUGGEST that the sidewalks/pavements are biased in some evil way.

    Society is complex, supposedly academic exercises like this DUMB superficial analysis is not sufficient to explain anything.

  5. David Nataf says:

    This analysis is not dumb, it’s quite useful.

    Whereas a lot of physical scientists believe that only work in math, physics, chemistry, etc is important, sociology is actually an extremely important field. We know that there is discrimination in society, and it’s not a fully-explained phenomenon. That is part of why it is important to have measurements of discrimination.

    This study is quite good, notice that it looks at multiple demographic groups and is thus extremely informative. It teaches us things we don’t already know: that Chinese females and Indian males are the most discriminated against, though I wish they had error bars. That’s the kind of information society needs to know if we are to acquire a superior understanding of discrimination and maybe even a means to tackle it.

  6. James Gallagher says:

    It’s useful to idiots who want to create some stupid political agenda.

    Reasonable people realise that you can’t analyse society in this stupid manner the same way you can’t analyse the weather in such a simple way (and make sensible predictions/conclusions)

    Because it’s much more complicated than these stupid graphs attempt to show.

  7. Charon says:

    @31: James, is it too much to ask you actually think about this? Experiments like this are useful because they isolate effects. Explaining why, say, blacks compose a substantially smaller proportion of the physics faculty at US universities than of the general population is a very difficult question with many factors. What studies like this show is that even controlling for many factors, there is still a racial (and gender) bias. Studies that send out identical CVs for review are great this way. They take away all the arguments like “blacks had inferior access to education K-12 which just propagates on”, etc.

    Every science became a real science the moment it learned to analyze simple systems first, and isolate interesting behavior before attempting more complex systems. Aristotle failed to get anything right in physics because he was trying to explain whole complicated systems at once (like you ask us to do). Galileo, on the other hand, succeeded because he said, “ignoring air resistance and friction and the curvature of the Earth…”

  8. “One thing to take note is that prospective students who are Indian or Chinese have historically been foreign students.”

    Indians are foreign? They’re Native Americans. Oops, wrong Indians. I actually thought it was talking about Indians as in Apache, Navajo, Choctaw etc.

    And before someone accuses me of being politically incorrect, I’m with Chris Eyre who said that “Indians call Indians Indians”. (Full disclosure: I am part Indian.)

  9. James Gallagher says:

    @Charon #32

    France has a policy that doesn’t allow statistics based on racial criteria. There is at least one good reason for this (besides the good intentions not to label people). If you are going to allow publication/study of statistics based on racial criteria then they are potentially misleading if you are BIASED in what types of statistics you choose to (allow to) publish.

    For instance, the above charts might suggest that Indians and Chinese are not well represented at universities, when the opposite is the case. But trying to discuss with someone why asians dominate in Berkeley admissions will soon lead to politically sensitive areas that could end up getting you labelled (by colleagues) in a potentially damaging way.

    There is bias everywhere, particularly in left-wing blogs and publications

  10. ERose says:

    @James –

    I guess I’d note the following – if members of any marginalized group explain the bias they personally face, there’s always more than one person who insists that they are too intellectual to accept “anecdata.” So when someone attempts to find some harder data there is always that one guy who insists the study is just too flawed to be valid because it doesn’t control for every “what-if” he can come up with.
    Sure there is room to build on this work, to refine it and to investigate the conclusion further – that’s the point of peer review. No one’s asking you to accept this study as having every single answer on this topic, and it’s intellectually lazy to engage with any scientific work only in that framework. The process of scientific study is a matter of gaining data one experiment at a time, and testing conclusions with subsequent experiments that approach the issue from a slightly different angle. That’s actually the right way to do it.
    Does this study seem to support the experiences that millions of individuals could and do describe? Yes. That’s only one solid reason the issue merits further study. Another is that millions of individuals have described things like this for a very long time and we’re only now getting around to looking for empirical data to convince people who don’t want to hear them.

  11. Robert says:

    Sean, since you state that “the results pretty much speak for themselves,” could you give us your thoughts on why there seems to be essentially no bias against Hispanic females in this study? This makes me think there’s something seriously wrong with the study.

  12. JesseB says:

    Why is Fine Arts at the bottom of the chart? It’s the third most biased group in the study; it should be third from the top.

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  14. Diversity says:

    In surveys of psychologists a large portion of academics admitted to actively discriminating against conservatives in hiring, review, and tenure decisions:

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