I'm a (male) PhD student at Caltech, and didn't really believe gender bias was prevalent in academia till I spoke with female friends and learned about the kind of problems they faced. Believe me people, the problem is real.
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Hi ,
* said that you can help me collect some data for the finance hiring committee. Here is what I need.
Attached is an excel spreadsheet with a list of business schools. Please go to each business school's website, and look up the finance department/area/group, and count the # of assistant professors in that group. In addition, please note the name of any assistant professor who is female or African-American, and the year of PhD if available. I hope you can complete this task by . Please let me know if you have any questions.
Best regards,
*
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Interestingly (in a sad way), I couldn't find any African American assistant professor professor in the list of ~100 schools I got for that field (although I did find "African Africans" and "African Europeans" or whatever you call being black and not American).
African Americans have internalized their class status so much, copying 'white people' has become equivalent to not being black.
That leads to a question not often discussed. I have seen in other places too that black people that are from outside US fare better in US than African-Americans. Is there a point in which the years lived under systemic racism have side effects of learned helplessness that amplify and perpetuate the initial problem?
Isn't that one aspect of learned helplessness?
Someone from Africa would only have some of the cultural markers we look for when making racial distinctions in America, so in this way they would be partially spared. Sometimes all it takes is some indication that this black person is "not like all the other black people" for someone to be open to the idea they are a capable and safe human being.
Our prejudices are not simple. We are not stupid, we are very good at seeing patterns. And evidence for intra-racial distinctions is not evidence against interracial distinctions.
It would be nice if you provided concrete examples, because I've had very much the opposite experience as you. From my perspective the problems are grossly exaggerated.
I guess we should all go ahead and believe him. I mean he did write a comment on the internet which consisted of some form of empty hearsay. That's all the proof any of us should need.
He said, while providing no concrete examples :)
Please catalogue your evidence with citations whenever possible, and make sure you use reputable sources. Please also disclose your precise statistical procedure and experimental setup so that we may assess the validity of your findings. The questionnaires that you have given to women to assess their satisfaction are also of interest, as changes in wording can elicit different responses. I hope your experiment procedure has controlled for that.
Person A: "I observe a bias".
Person B (me): "Please show me the bias. I haven't seen it."
You (to me): "Prove that you don't observe a bias".
Christ, the level of discourse in these conversations is abysmal. We've reached the point where asking for citations is met with the response of "citation needed".
Sure, you can nitpick over the use of the word prevalent, but it's quite clear from the context that the conclusion was drawn on basis of the experience described (other than the article).
Anyway you want to cut it, this is a completely pedantic derailment of the original point: OP is making completely empty declarations.
You didn't only disbelieve his statement, you offered a different claim.
If things are not equal, you can still prove that there is no bias by asking the disadvantaged group for their opinion. It's not like polling this group is impossible.
Statistics do not work like this. You either positively reject the null hypothesis (i.e.: "these things are different") or you fail to reject the null hypothesis (i.e.: "I cannot assert these are different").
Formally speaking, I am doing the latter.
Informally speaking, everybody else understood my point as a rebuttal to OP's. More explicitly: "claims of X seem grossly exaggerated" should be taken as "I haven't seen compelling evidence for X" -- it may be awkwardly phrased, but I suspect you know exactly what I meant.
You can also just outright swap around your null and alternative hypotheses for a frequentist-style test. For example, your null hypothesis could be "proportion of women to men is 0.1" and your alternative hypothesis is that it isn't, for a standard two-tailed test.
* Well, other than maybe the word 'belief', but this isn't clear imo
In which case I'll reiterate my request that he provide examples, since I've not observed the effect he seems to see all around him.
If so, that would be an extremely unusual thing for a human being to do, and I would wonder what would motivate someone to ask that kind of question.
My aim was to inspire thinking.
I agree that a methodologically sound experiment in the social sciences would be an unusual thing to do. But should we let the perfect be the enemy of the good? Or, to put it differently, if you are in the market for a second-hand automobile, would you trust the used-car saleswoman's word, or wonder if she has ulterior motives?
Would you care to elaborate, or are you just being flippant?
> if you are in the market for a second-hand automobile, would you trust the used-car saleswoman's word, or wonder if she has ulterior motives?
A used car salesperson's motives are crystal clear, which is why their opinion is justifiably taken with a pinch of salt. You seem to be suggesting by comparison that women have an equally uncomplicated incentive to lie. Don't misunderstand, I think people do lie, especially to themselves, but I also think the evidence shows that discrimination is part of human nature.
Considering that this kind of experience lines up with both anecdotal evidence and with studies of unconscious bias in related areas [0][1][2][3][4] my default position is to assume that a problem is reasonably likely, but that further data would be useful.
[0] Female students seen as less competent than identical male students with identical application materials, offered lower starting salaries (Moss-Racusin et al, 2012)
[1] People in gender-incongruent roles penalised more heavily for mistakes (Brescoll, Dawson, & Uhlmann, 2010).
[2] Voluble women perceived as less competent and less suitable leaders, inverse true for men (Brescoll, 2011).
[3] Women who succeed in male-dominated fields percieved as not likeable (Heilman et al, 2004).
[4] Students question the competence of female teachers who evaluate them negatively, less so than male teachers (Sinclair & Kunda 2000).
...and yes, repeatability is an issue. That's a systematic problem.
Would you care to elaborate
Anyway, we both agree on the systematic repeatability problem in social sciences.
A used car salesperson's motives are crystal clear,
which is why their opinion is justifiably taken
with a pinch of salt.
uncomplicated incentive to lie.
Yes. I am currently doing a lot of work on exactly that subject.
> A gender studies researcher's motives are crystal clear...
...and we're not discussing the motives of gender studies researchers. We're discussing a man talking to his friends about their own experiences. You were the first one to bring up the topic of social science.
we're not discussing the motives of gender studies researchers.
As to you "doing a lot of work on exactly that subject", what are the results? Why do you, like a lot of men, automatically genuflect to damsels, going on about their distress?
You seem to be implying that a significant portion of discrimination is (by fair means or foul) invented, on the basis that women have a motive to do so.
By that same logic, a significant portion of men would therefore refute and deny any genuine stories of discrimination, as they have a motive to do so.
The best way to unpick this stuff is with actual data, and there's plenty of data (from labs, randomised controlled trials, and other types of study) that says discrimination is still occurring at a systematic level.
> You brought up gender studies researchers by referencing material of questionable scientific credibility.
Feel free to offer some thoughtful analysis of the actual papers mentioned.
> As to you "doing a lot of work on exactly that subject", what are the results?
To be published when ready.
> Why do you, like a lot of men, automatically genuflect to damsels, going on about their distress?
That would be empathy, Bob.
You seem to be implying ...
Do you agree or disagree?
By that same logic ...
there's plenty of data
Feel free to offer some thoughtful analysis of the actual papers mentioned.
Just like that? Without any examples or data?
Do you really expect people to just listen and believe?!
Edit: typos.
There seems to be an underlying conclusion that men can't understand what women face and are blind to their privilege, but that women can understand the problems men face and are not blind to their privilege.