My understanding is that the correlations in question persist, and are not small, when those other things are either controlled for or taken out of the picture. For example, here is an informal writeup of a PNAS article finding evidence of bias favouring male over female job applicants when everything about the applications was exactly the same apart from the name.
There are even clearer examples of gender bias on the unconscious level. The fact that women are hired at equal rates as men by orchestras if, and only if, the audition is behind a curtain and everyone enters barefoot so the hiring committee cant tell gender by footstep sounds is the most damning I can think of right now. Because that is a straight up test of competence at the only skill relevant for the job, and applicant genitalia still sway supposed experts unless extreme measures are taken to blind them to that factor. Basically, at this point there is such a huge pile of evidence that human beings are just completely incompetent at screening out utterly irrelevant factors that I would judge it sensible hiring policy in any field to have the job interview behind a curtain and a vocoder.
… Fuck it, I’m using that in a story. It fits right into a certain culture I’m building. ;)
I would not recommend conducting hiring tests for an orchestra behind a vocoder :-).
(Other than that: yes, I agree, except that actually conducting hiring interviews that way would probably actually lose more signal than it eliminated noise, at least in the fields I’m familiar with interviewing in. Alas.)
(Other than that: yes, I agree, except that actually conducting hiring interviews that way would probably actually lose more signal than it eliminated noise, at least in the fields I’m familiar with interviewing in. Alas.)
Software development, engineering, mathematics (in industry rather than academia).
The loss of signal could probably be eliminated in all of these, with some effort. The sort of thing I’m thinking of where signal would be lost by default is where you ask the interview candidate to design something, write a bit of code, sketch a system they worked on in the past, etc., on paper or whiteboard. If the candidate has to be behind a curtain, that’s difficult to do and probably involves irksome extra latency (e.g., a system where they write or sketch whatever they want to and then step aside, and only then does the interviewer get to see what they did).
You could work around this with computerized whiteboards—the candidate sits in one room and the interviewers in another, both rooms have electronic whiteboards, and they are coupled so that anything written on one shows up on the other too.
(Or by using something other than whiteboards that’s easier to decouple in this way. For instance, for a coding task some kind of collaborative text editor may do better.)
I see. (I had guessed you were talking of people who have to directly¹ interact with perspective customers, so you have to know what they look and sound like in order to know what first impression perspective customers might get.)
Of course what “directly” means depends on where you are; I hear there’s a country where people will boycott a Web browser solely because of the political stance of the CEO of the company making it on a topic with hardly anything to do with software. ;-)
Yes, that would be another example. But, I think, a different sort of example. Let’s suppose that candidate A comes across better than candidate B in interview simply because of widely-shared prejudices affecting the interviewers. For the kind of job you describe, that (rather horribly) means that candidate A probably is better able to do the job than candidate B.
(It might well be that the best thing overall is to try to stop people in that situation favouring A over B on account of prejudice anyway, in the hope that over time this reduces the overall level of prejudice and everyone is better off.)
There is a really nifty way to solve this, by the way. Do what the Norwegians do. Half of maternity leave accrue to the other parent and is non-transferable.
That way career impact of child birth becomes gender neutral—for anyone married, anyways.
And like all the best of feminist ideas, it is irreversible policy because it benefits both genders.
Men get time of to spend some time with their kid, and women don’t have to worry about potential employers shunning them out of fear of having them go on leave because potential employers cannot hire anyone without that risk attached. Well, post menopausal women, I suppose. Doesn’t seem likely to become a dominant hiring strategy.
Half of maternity leave accrue to the other parent and is non-transferable.
Of course, maternity leave isn’t the only way in which women can chose family over career. Also, this kind of policy amounts to valuing “equality” for its own sake above everything else, like productivity.
.. Norway has labor productivity 35 percent higher per hour worked than the us does. They work a bit less, so the country as a whole is only 27% percent richer than the US is. Yhea, this is really a policy that dings economic productivity.
Also, basic logic: What is the contribution to the formal economy of a woman who can’t find work due to gender discrimination?
Norway has labor productivity 35 percent higher per hour worked than the us does
Sigh. Do you bother to check your numbers?
In 2013 the productivity in Norway was 62.6 GDP/hour while in the US it was 57.5 GDP/hour (source). And I bet that’s the consequence of the fact that a large part of Norway’s economy is offshore oil and gas which are highly capital intensive and so generate very high productivity.
Note that in Sweden, a country with social policies broadly similar to Norway’s but without the oil, the productivity is 45.0 which is noticeably lower than in the US and is close to the EU average.
the country as a whole is only 27% percent richer than the US is.
The country as a whole is much poorer that the US because it is much smaller. I suspect you meant things like GDP per capita which for Norway is indeed higher that for the US (again, because Norway has a small population and pumps a lot of oil out of the North Sea).
I was using the OECD databases, except I was not using 2005 PPP to compare 2013 gdp. Which is what is in your link. Setting the exact same table to compare against the US as the hundred percent baseline gives a number for Norway of 130.2 Which isn’t what I got from the table I was using, so obviously the OECD doesn’t agree with itself at all times o,O Oh well.
Further checking the OECD quickly, no, the lead isn’t down to petroleum alone—absurdly high in all sectors, save agriculture. Which is mostly down to Norway being an idiotic place to grow crops.
And that lead is growing, so it is not a legacy—their current policies are successes.
If oil has anything to do with it I strongly suspect that it is via indirect political effects—No Norvegian politician can implement austerity or embark on a campaign to suppress wage growth due to the oil money, so the country doesn’t shoot it’s own economy in the knee on a regular basis like the rest of the west does.
But never mind statistics. Do you have issues with the basic logic?
“Policies that remove gender based barriers to employment are good for the economy, due to the basic fact of life that housewife is a ludicrously low-productivity job sector”.
Heck, near as I can tell, a good chunk of the wealth gain’s of the past 50 years has mostly been the working out of the productivity implications of household appliances − 2 income households are possible because the electric stove, the refrigerator and the vaccum means keeping house isn’t a full time job.
Re: Being poorer than the US due to smaller size. That isn’t how people use the word rich. Depending on which statistics you use, China has an economy which either is, or will shortly be, larger than the US one. Would you consider it reasonable to refer to China as richer than the USA once that absolute size becomes indisputable?
“Policies that remove gender based barriers to employment are good for the economy, due to the basic fact of life that housewife is a ludicrously low-productivity job sector”.
What do you mean “remove gender barriers”? Do you mean policies requiring companies to hire be “non-sexist” in their hiring practices etc.? Because if those practices increased productivity companies would use them anyway.
Heck, near as I can tell, a good chunk of the wealth gain’s of the past 50 years has mostly been the working out of the productivity implications of household appliances − 2 income households are possible because the electric stove, the refrigerator and the vaccum means keeping house isn’t a full time job.
Also have both spouses work tends to result in the couple having a lot fewer children. In fact in another thread people were complaining that they couldn’t afford to have kids because they couldn’t subsist on one income.
I don’t think that distinction matters much to the point Azathoth123 is making. (Personally I’d put the family in that thread in the grey area between “couldn’t subsist on one income” and “maybe could but it would be terrible”. Husband and wife on $10k/year each. I wouldn’t want to try supporting a family of three on $10k/year, though maybe it could be done if “supporting” means “living on the streets and barely managing to feed” or “scraping by using every bit of government-supplied assistance available”.)
I wouldn’t want to try supporting a family of three on $10k/year
I wouldn’t want to support a family of one on $10K/year. But I think the context of this discussion is that the middle class feels the need for two incomes and so the wife works instead of being a housewife.
What do you mean “remove gender barriers”? Do you mean policies requiring companies to hire be “non-sexist” in their hiring practices etc.? Because if those practices increased productivity companies would use them anyway.
Unless there’s some kind of PD-like situation whereby sexist hiring practices benefit your company to the expense of everyone else’s.
Further checking the OECD quickly, no, the lead isn’t down to petroleum alone—absurdly high in all sectors, save agriculture.
Link to numbers, please..?
But never mind statistics.
I am sorry, I’m going to mind statistics. You seem to like numbers when they support (or can be made to support) your predefined conclusion, but when it turns out your statistics are wrong or misleading you go “never mind”.
Do you have issues with the basic logic?
Yes, because you can’t run a cost-benefit analysis without looking at costs.
That isn’t how people use the word rich.
That is how people use the expression “country as a whole”.
That is how people use the expression “country as a whole”.
Is a ton of air as a whole denser than a gram of gold as a whole? IOW intensive quantities are intensive.
Is “rich” an intensive quantity, like “dense”, or an extensive one, like “heavy”? Meh. I’d say it depends on the context, and in the context of Izeinwinter’s comment I’d say it is clear which they meant.
Because an unspoken condition of employment that prospective employees must stay single is a management technique made of win.
Errh.. Not. Good lord. would you want to manage a team made up of 100% celibate men? This is not a weakspot in the law, because it’s not a runaround anyone sane enough to not already be bankrupt would attempt.
It might on the margin inspire people to hire more people in their forties and fifties, - people who have had any children they are likely to have, but from the point of view of the government, that’s also not a flaw, but more of a “Secondary benefit free with just legislation”.
Obviously not. Equally obviously, said likelihood has no bearing on the applicant’s competence, which was rated substantially and significantly lower by the faculty in the study when the application bore a female rather than a male name.
(Good statistics on this seem hard to come by, but it looks like the average age at first birth for college graduates in the US is about 30 nowadays; I’d say the probability of an imminent maternity leave for a 22-year-old with a new job as a lab manager in a university is pretty damn small, even if she happens to be called Jennifer rather than John.)
For example, here is an informal writeup of a PNAS article finding evidence of bias favouring male over female job applicants when everything about the applications was exactly the same apart from the name.
That’s not necessarily irrational in general. The other information on the resume does not prevent the name from also providing potentially relevant information.
I’d suggest you look up “screening off” in any text on Bayesian inference. The explanation on the wiki is not really the greatest.
But when you have information that is closer and more specific to the property you’re trying to predict, you should expect to increasingly disregard information that is further from it. Even if your prior asserts that sex predicts competence, when you have more direct measures of competence of a particular candidate, they should screen off the less-direct one in your prior.
I’d suggest you look up “screening off” in any text on Bayesian inference. The explanation on the wiki is not really the greatest.
I know what screening off is—I was saying that not all the information is screened off here. There are still other issues given the premise that names taken alone predict competence to some extent. For example, one resume may be more likely to be honest than another, and even if the resume is completely honest, reversion to the mean is likely to be larger in one case than another.
So: take a look at the paper, or at the informal summary of it to which I also linked, and then tell us whether you consider that—given all the information provided to the faculty in the application—knowing whether the candidate is male or female gives anywhere near enough further information to justify the differences in rated competence found by the researchers.
It seems to me that for that to be so, there would need to be absolutely huge differences between men and women, so big that no one with any brain and any integrity would deny that men are much much much better scientists than women. Do you think that’s the case?
It seems to me that for that to be so, there would need to be absolutely huge differences between men and women, so big that no one with any brain and any integrity would deny that men are much much much better scientists than women. Do you think that’s the case?
I think that regardless of the actual facts, assuming the difference is counterfactually that large, it’s still very plausible that almost everyone would still deny any difference exists, due to political and cultural forces.
While I don’t think there is such a large difference, I don’t accept the argument from “people wouldn’t pretend a big difference doesn’t exist”.
I wasn’t merely arguing that if there were such a large difference everyone would admit it. I was also arguing that if there were such a large difference we’d all know it. Obviously this argument will be more persuasive to people who (like me) think it’s clear from observation that there isn’t so huge a difference between men and women, than to people who don’t.
Just by way of reminder: we’d be looking for a difference large enough that, knowing
what degree a person got from what institution
what their grade point average was
what their GRE scores are
what was written about them by a faculty member writing a letter of recommendation
what they wrote themselves in an application letter
the difference between male and female suffices to make a difference to their estimated competence of 0.7 points on a 5-point scale. That would have to be either a really really enormous difference between men and women, or a really weird difference—weird in that whatever it is somehow manages to make a big difference in competence without having any effect on academic performance, test scores, or reported faculty opinions. Which presumably would require it to be quite narrow in scope but, again, really really enormous in size.
And it seems about as obvious to me that there isn’t such a difference as that (say) there isn’t a difference of 20cm in typical heights between men and women. Not just because if there were then it would be widely admitted (maybe it would, maybe not) but because it would be obvious.
Now, of course I could be wrong. There could be such an enormous difference and I could be somehow blind to it for some weird cultural-political reason or something. But is it really too much to suggest that when
the exact same job application gets radically different evaluations depending on whether the candidate’s name is “John” or “Jennifer”
it’s reasonable to take that as strong evidence for bias in favour of men over women that isn’t simply a proportionate response to actual differences in competence? I mean, it’s just Bayes’ theorem. How likely is that outcome if people do have such bias? How likely is it if they don’t? (Not “is it possible if they don’t?”. The answer to that sort of question is almost always yes, regardless of what’s true.)
I wasn’t merely arguing that if there were such a large difference everyone would admit it. I was also arguing that if there were such a large difference we’d all know it.
It’s not entirely clear that these are two different things. Admitting a highly politically incorrect opinion publicly and admitting it to oneself or one’s friends aren’t really completely separate. People tend to believe what they profess, and what they hear others profess.
That would have to be either a really really enormous difference between men and women, or a really weird difference—weird in that whatever it is somehow manages to make a big difference in competence without having any effect on academic performance, test scores, or reported faculty opinions. Which presumably would require it to be quite narrow in scope but, again, really really enormous in size.
I suspect one source of the disagreement between us may be that you’re assigning a high predictive ability to academic performance, while I don’t even assign it a very high correlation. This may be because my intuition is trained on different academic fields. I don’t have any experience with scientific lab managers (the job the study’s resumes applied for). I do have experience with programmers and other related fields, mostly below the doctoral level.
And it seems about as obvious to me that there isn’t such a difference as that (say) there isn’t a difference of 20cm in typical heights between men and women. Not just because if there were then it would be widely admitted (maybe it would, maybe not) but because it would be obvious.
When I first read that I thought: but there is about a 20cm difference in the average heights of men and women! Is gjm arguing the opposite point from what I thought, or maybe being sarcastic?
So I checked the average height differences between the sexes, and the male:female ratio is typically between 1.07-1.09. This translates to 8-15 cm of difference. So while it’s not as much as 20cm, it’s “only” a 2x difference from my prediction. Maybe I’m just bad at translating what I see into centimeters and this difference is much more obvious to you than it is to me.
But is it really too much to suggest that when the exact same job application gets radically different evaluations depending on whether the candidate’s name is “John” or “Jennifer” it’s reasonable to take that as strong evidence for bias in favour of men over women that isn’t simply a proportionate response to actual differences in competence?
I don’t disagree with this. I just think the cultural power of “politically correct” thinking is strong enough to make people ignore truths of the magnitude of this being counterfactually wrong and stick to accepted explanations.
So I checked the average height differences between the sexes, and the male:female ratio is typically between 1.07-1.09. This translates to 8-15 cm of difference. So while it’s not as much as 20cm, it’s “only” a 2x difference from my prediction. Maybe I’m just bad at translating what I see into centimeters and this difference is much more obvious to you than it is to me.
Maybe gjm’s System 1 automatically compensates for the difference—I know that unless I’m deliberately paying attentìon to people’s height I’m much less likely to notice it if a man is six feet tall than if a woman is six feet tall, and for all we know the same might apply to gjm.
Yeah, I know, people consider my barely basic¹ cooking skills exceptional merely because I happen to have a Y chromosome. That’s male privilege for ya.
At least that’s what my System 1 tells me, and I can’t think of a way to find out whether the impostor syndrome applies short of having someone who doesn’t know my gender taste what I cook.
you’re assigning a high predictive ability to academic performance, while I don’t even assign it a very high correlation.
Academic performance is one of the things known to the faculty (and the same between the “male” and “female” conditions); it is not the only one. The relevant question is: How much predictive power does the totality of the information provided have, and conditioned on that how much predictive power does the sex of the applicant have? It looks to me as if the answers, on any account of sex differences that I find credible, are “quite a bit” and “scarcely any”.
By “academic performance” I was referring to all of these bullet points:
what degree a person got from what institution
what their grade point average was
what their GRE scores are
what was written about them by a faculty member writing a letter of recommendation
Which (from your summary) I understand is pretty much all of the information in the application letter.
I’m not claiming that sex differences have predictive power; I’m claiming that academic performance doesn’t have as much power as we’d like and recruiters have to look for more info.
For sure. My apologies if I somehow gave the impression of disagreeing with that. The second half of what I called the “relevant question” above is of course the real key here, and it sounds as if maybe we agree about that.
Obviously this argument will be more persuasive to people who (like me) think it’s clear from observation that there isn’t so huge a difference between men and women, than to people who don’t.
No. If the argument is more clear because you think that it supports the outcome that you prefer you are engaging in motivated cognition. It’s an error in reasoning.
But I didn’t say, and I don’t think it’s true, that the argument is clearer “because [I] think it supports the outcome [I] prefer”. I “prefer” that outcome, in part, because it seems clear from observation that there isn’t that sort of huge difference between men and women. That is not a reasoning error, it’s straightforward inference.
So your theory is that all observed larger number of men at the upper end of any bell curve is due to sexism? And the larger number of men at the lower end of most bell curve, e.g., more men in prison is due to..something?
Most of the data I’ve seen suggests women have lower variance, here Robin Hansen discusses some of the implications about variance in test scores.
There may well be differences in average performance between men and women in various intellectual tasks, in either direction. Indeed, there are some specific categories of tasks where the evidence for such differences seems strong; the most famous example is probably “mental rotation”. The difference for mental rotation is large but not enormous (about 1sd); my understanding is that all other sex differences found in scientific studies are smaller, and there are differences going in both directions.
It seems unlikely to me that there’s a big general cognitive deficit on either side. I believe girls are currently doing better than boys in pretty much all subjects at school in my country nowadays; in the past it was the other way around; so whatever differences there are (in this kind of task) must be smaller than the size of difference that can be induced by cultural effects. Of course this is consistent with deficits in very specific areas, with variance differences that affect how many really stellar performers there are of each sex, etc.
There may well be differences in variance between men and women. These differences might be fairly big, but it seems unlikely to me that they’re large enough to make huge differences at “ordinary” ability levels.
Once you start looking at the tails of the distributions, I expect them to be quite far from being Gaussian or even symmetrical. There are a lot more ways for things to go badly wrong than for them to go exceptionally right, after all. So I am skeptical about inferences from differences at the “low” end to differences at the “high” end.
There are certainly a lot more men than women in prison, especially if you look specifically at crimes of violence. However, lumping this together with variations in ability seems like a wilful embracing of the halo/horns effect; it seems like much of it will come from variations in sociopathy, enjoyment of violence, and other such characteristics that needn’t go along with worse performance as (say) a scientific lab manager.
For those last two reasons, any inference that looks much like “there are more men in prison, so we should expect more men to win Nobel prizes in physics” seems extremely suspect to me. Still more “there are more men in prison, so we should expect more men to make good lab managers”.
Putting all the above together: there may be well be differences in competence between men and women; they may well be bigger at the highest levels; I wouldn’t expect the differences to be enormous except maybe at the very highest levels where variance differences can be a really big deal.
All of that is independent from the question of whether there are sexist attitudes—by which, for present purpose, I mean: whether there are systematic biases that make men get evaluated better than women relative to their actual ability, likely performance, etc. Or, for that matter, worse.
It seems to me that there is a lot of evidence that there are such sexist attitudes, generally favouring men over women. We’ve had a lot of discussion of one study which seems to me like very strong evidence for such attitudes in one domain; I posted some links to some others. There’s a pile of anecdote too, but of course the way that looks may simply reflect what anecdotes I happen to have encountered. (I think the available anecdotage is at any rate evidence that sexist attitudes in both directions exist.)
The possibility of real ability differences has some bearing on how to interpret the apparent evidence for sexist attitudes, but in at least some cases—e.g., the study we’ve discussed so much here—it seems to me that it doesn’t make much difference, because to make the evidence not be strong evidence for sexist attitudes it would be necessary for the ability differences to be (what seems to me to be) unrealistically large.
The relevant question for most practical purposes is not the statistical difference between men and women in some particular kind of ability, but the statistical difference conditional on the information usually available when hiring (or when considering promotion, or when allocating places at a university, or whatever). Nothing I have seen so far gives me reason to think that these differences are large, even though the information in question is limited and unreliable.
(To get quantitative for a moment, let’s suppose everything in sight is normally distributed. Some underlying ability: male and female both have mean 0, but s.d. 1 for men and 0 for women. Some measure of ability equals the actual ability level plus noise with mean 0 and s.d. 1. Actual job performance looks like underlying ability plus other factors with mean 0 and s.d. 0.5. Then conditional on measured ability being +2 (i.e., well above average but not stratospheric), mean predicted job performance is about +1.0 for male applicants (with s.d. 0.87) and +0.8 for female applicants (with s.d. 0.80), a difference of about 0.2 (male) standard deviations. Definitely not zero, but not exactly huge either and a lot smaller than the noise. I have no idea how realistic any of the numbers I’ve assumed here actually are, and would be glad to learn of credible estimates—though of course this is a toy model at best whatever numbers one plugs in.)
Thanks. Though that high likelihood of mindkill makes it (1) more likely that someone will try to correct my obvious stupid errors when in fact I’m right and they’re confused, and (2) more likely that someone will rightly correct my obvious stupid errors when in fact they’re right and I’m confused but I won’t believe them. Still, the best we can do is the best we can do :-).
There are certainly a lot more men than women in prison, especially if you look specifically at crimes of violence. However, lumping this together with variations in ability seems like a wilful embracing of the halo/horns effect; it seems like much of it will come from variations in sociopathy, enjoyment of violence, and other such characteristics that needn’t go along with worse performance as (say) a scientific lab manager.
Note that the number of people who are in jail doesn’t merely depend on how many commit crimes, it depends on how many get caught committing crimes, and that such a statistic would anticorrelate with intelligence is very nearly obvious to me.
Yes, that’s a good point. How big the effect is depends on how the probability of getting caught varies with intelligence: I agree that it will almost always anticorrelate, but the dependence could be very strong or very weak. Anyone got any statistics on that?
Hmm. It might be possible to indirectly get some information about them by comparing the kinds of people that get caught for premeditated crime with the kinds of people that get caught for crimes of impulse, and then adjusting for any correlation of intelligence with self-control. The latter ought to be harder to cover up.
It quite easy to make wrong arguments in favor of positions that are true. If you think that an argument is good just because you think it’s conclusion is true it’s time to pause and reflect and look at a situation where the same structure of the argument would lead to a conclusion that’s false.
Even if men and woman are on average equally qualified that doesn’t mean that a specific subset is. For a hiring manager it’s not important whether there’s causation. Correlation in the data set is enough.
If you think that an argument is good just because you think its conclusion is true [...]
I agree, that’s a very bad sign. On the other hand, there’s nothing very alarming about thinking an argument is more persuasive when you agree with its premises. And often the premises and the conclusions are related to one another. That seems to me to be exactly the situation here.
Premise: There pretty clearly isn’t an enormous cognitive difference between men and women that makes women much less competent at brainwork, so much less competent that a moderate amount of information about a person’s abilities leaves a lot of male-female difference un-screened-off.
Argument: If indeed there isn’t, then the best explanation of findings of the sort we’ve been discussing is prejudice in favour of men and against women that has substantial impact on hiring.
Conclusion: There probably is such prejudice, and it probably leads (among other things) to underrepresentation of women in many brainwork-heavy jobs.
(Note: the premise, the argument, and the conclusion are all sketchy approximations. Filling in all the details would make the above maybe 20x longer than it is.)
I find the argument somewhat persuasive. This is partly because I find the premise plausible; some people might not (e.g., because the evidence they think they have regarding the relative abilities of men and women differs from the evidence I think I have); those people will find it less persuasive.
The premise in question is not the conclusion of the argument. It is not equivalent to the conclusion of the argument. It neither implies nor is implied by the conclusion of the argument. It is, for sure, somewhat related to the conclusion—e.g., by the fact that they are premise and conclusion of a short and simple argument—and doubtless there is a correlation between believing one and believing the other. I do not find this sufficient reason to think that finding the argument more credible if one accepts the premise is any sort of cognitive error.
Perhaps I am misunderstanding your argument somehow. I confess I don’t find it perfectly clear. Would you like to make it more explicit what error you think I am committing and why you think that?
Even if men and women are on average equally qualified that doesn’t mean that a specific subset is.
I agree and am not aware of having said or implied otherwise. One of the many modifications that would be needed to turn the argument-sketch above into something unambiguous and quantitative would be to replace “between men and women” with “between men applying for lab manager posts and women applying for lab manager posts”. If you think this makes an actual difference in here, I’d be interested to see the details.
For a hiring manager it’s not important whether there’s causation. Correlation in the data set is enough.
Depends on the details, of course, but mostly yes. Once again, though, I am having trouble working out what I’ve said that suggests I think otherwise.
If the argument is more clear because you think that it supports the outcome that you prefer you are engaging in motivated cognition.
And/or if the argument is less clear to other people because they think it supports the outcome that they don’t like they are engaging in motivated cognition.
it’s reasonable to take that as strong evidence for bias in favour of men over women that isn’t simply a proportionate response to actual differences in competence? I mean, it’s just Bayes’ theorem. How likely is that outcome if people do have such bias?
By the same logic you could say that someone who hires people with high SRT scores engages in SRT bias. Someone who hires based on SRT scores could simply reasonably believe that people with high SRT scores are more competent.
Google’s HR department has a variety of factors on which it judges candidates. A few years afterwards they reevaluate their hiring decisions. They run a regression analysis and see which factors predict job performance at Google. They learn from that analysis and switch their hiring decision to hiring people which score highly on the factors that the regression analysis found predictive.
That’s how making rational hiring decisions looks like. In the process they found that college marks aren’t very relevant for predicting job performance. Being good at Fermi estimates unfortunately isn’t as well, so those LW people who train Fermi estimates don’t get benefits anymore when they want to get a job at Google.
Given current laws Google is not allowed to put values such as gender into the mix they use to make hiring decisions. That means that Google can’t make the hiring decisions that maximize predicted job performance.
The politics of the issue also make it pretty bad PR for them to publish results about the effects of a model that includes gender if the correct value in the regression analysis would mean worse chances for woman getting a job. It’s good PR for them if the correct value would mean to favor woman. No big company that does regression analysis on job performance published data that favoring in gender would mean hiring more woman.
Factoring in gender into a regression analysis would mean that any bias against woman in subjective competence evaluations in interviews would be canceled by that factor.
Just imagine if a big company would find that by putting gender into their regression analysis they would hiring more women and get better average job performance as a result. Don’t you think those companies would lobby Washington to allow them to put gender into hiring decisions? The silence on the issue speaks.
It could be that the silencing of feminists who want to prevent “privileged” from talking about the issue is strong enough that rational companies don’t dare to speak about their need to change their hiring practices to hire more woman via making data driven arguments. If that’s the case that says a lot about the concept of privilege and it’s problem in shutting down rational arguments.
weird in that whatever it is somehow manages to make a big difference in competence without having any effect on academic performance, test scores, or reported faculty opinions
Imagine that academic performance has a really low value for predicting job performance. People that spend a lot of time preparing for tests get better academic marks. Woman spent more time than men preparing for academic tests. That means a woman of equal competence scores higher because she puts in more work. The test isn’t anymore a strict measure of competence but a measure of effort at scoring highly of the test. In that scenario it makes sense to infer that a woman with the same test score as a man is likely less competent as the man as long as you are hiring for “competence” and not for “putting in effort to game the test”.
I mean, it’s just Bayes’ theorem. How likely is that outcome if people do have such bias? How likely is it if they don’t?
If you write down the math you see that it depends on your priors for the effect size of how gender correlates with job performance.
Imagine that academic performance has a really low value for predicting job performance. [...]
Sure. It is possible to construct possible worlds in which the behaviour of the academic faculty investigated in this study is rational and unbiased and sensible and good. The question is: How credible is it that our world is one of them?
If you think it is at all credible, then I invite you to show me the numbers. Tell me what you think the actual relationship is between gender, academic performance, job performance, etc. Tell me why you think the numbers you’ve suggested are credible, and why they lead to the sort of results found in this study. Because my prediction is that to get the sort of results found in this study you will need to assume numbers that are really implausible. I could, of course, be wrong; in which case, show me. But I don’t think anything is achieved by reiterating that it’s possible for the results of this study to be consistent with good and unbiased (more precisely: “biased” only in the sense of recognizing genuine relevant correlations) decisions by the faculty. We all (I hope) know that already. “Possible” is waaaaay too low a bar.
The question is: How credible is it that our world is one of them?
Making wrong arguments isn’t good even if it leads to a true conclusion. I haven’t argued that the world happens to be shaped a certain way. I argue that your arguments are wrong. LessWrong is primarily a forum for rational debate. If you arguing for a position that I believe to be true but make arguments that are flawed I will object. That’s because arguments aren’t soldiers.
On the matter of the extend of gender discrimination I don’t have a fixed opinion. My uncertainty interval is pretty large. Not having a small uncertainty interval because you fall for flawed arguments matters. The fact that humans are by default overconfident is well replicated.
But if we become back to grades as a predictor: Google did find that academic performance is no good predictor for job performance at Google.
Google doesn’t even ask for GPA or test scores from candidates anymore, unless someone’s a year or two out of school, because they don’t correlate at all with success at the company.
Of course Google won’t give you the relevant data as an academic does, but Google is a company that wants to make money. It actually has a stake in hiring high performing individuals.
While we are at it, you argue as if scientific studies nearly always replicate. We don’t live in a world where that’s true. Political debates tend to make people overconfident.
It looks to me as if that’s because you are treating them as if they are intended to be deductive inferences when in fact they are inductive ones.
At no point have I intended to argue that (e.g.) it is impossible that the results found in this study are the result of accurate rational evaluation by the faculty in question. Only that it is very unlikely. The fact that one can construct possible worlds where their behaviour is close to optimal is of rather little relevance to that.
Google did find that academic performance is no good predictor for job performance at Google.
Among people actually hired by Google. Who (1) pretty much all have very good academic performance (see e.g. this if it’s not clear why that’s relevant) and (2) will typically have been better in other respects if worse academically, in order to get hired: see e.g. this for more information.
I conjecture that, ironically, if Google measure again, they’ll find that GPA became a better predictor of job success when they stopped using it as an important metric for selecting candidates.
you argue as if scientific studies nearly always replicate
Not intentionally. I’m aware that they don’t. None the less, scientific studies are the best we have, and it’s not like there’s a shortage of studies finding evidence of the sort of sex bias we’re discussing.
None the less, scientific studies are the best we have
“Best we have” doesn’t justify a small confidence interval. If there no good evidence available on a topic the right thing to do is to be uncertain.
it’s not like there’s a shortage of studies finding evidence of the sort of sex bias we’re discussing
The default way to act in those situations is to form your opinions based on meta-analysis.
I conjecture that, ironically, if Google measure again, they’ll find that GPA became a better predictor of job success when they stopped using it as an important metric for selecting candidates.
You basically think that a bunch of highly paid staticians make a very trivial error when a lot of money is at stake. How confident are you in that prediction?
If there is no good evidence available on a topic the right thing to do is to be uncertain.
I agree. (Did I say something to suggest otherwise?)
The default way [...] is to form your opinions based on meta-analysis.
Given the time and inclination to do the meta-analysis (or someone else who’s already done the work), yes. Have you perchance done it or read the work of someone else who has?
I agree. (Did I say something to suggest otherwise?)
On this topic it seems like your position is that you know that employers act irrationally and don’t hire woman who would perform well.
My position is that I don’t know whether or not that’s a case. That means you have a smaller confidence interval. I consider the size of that interval unjustified.
Given the time and inclination to do the meta-analysis
In the absence of that work being done it’s not good to believe that one knows the answer.
My position is that I’ve seen an awful lot of evidence, both scientific and anecdotal, that seems best explained by supposing such irrationality. A few examples:
Another study of attitudes to hiring finding that for applicants early in their career just changing the name from female to male results in dramatically more positive assessment. (The differences were smaller with a candidate several years further into his/her career.)
A famous study by Goldberg submitted identical essays under male and female names and found that it got substantially better assessments with the male name. (I should add that this one seems to have been repeated several times, sometimes getting the same result and sometimes not. Different biases at different institutions?)
In each case, of course one can come up with explanations that don’t involve bias—as some commenters in this discussion have eagerly done. But it seems to me that the evidence is well past the point where denying the existence of sexist biases is one hell of a stretch.
I’m not really commenting on the object-level issue, just on the dubious logic of claiming that the name can’t matter if everything else is equal. In practice I’d guess it’s likely that the difference in rating is larger than justified.
Just that if you asked, ahead of time, a question like “So, what would it take to convince you beyond reasonable doubt that there’s bias favouring men over women in the academic employment market?”, the answer you’d get would likely be pretty much exactly what this study found.
Of course, there are always loopholes, just like a sufficiently ingenious creationist can always find contrived explanations for why some scientific finding is compatible with creationism. The speed of light is changing! The aftermath of Noah’s flood just happened to deposit corpses in the layers we find in the fossil record! The world was created with the appearance of great age! Similarly, we can find contrived explanations for why an identical-looking application gets such different assessments depending on whether it’s thought to come from a man or a woman. They might be really worried about maternity leave, and choose to define taking maternity leave as a variety of incompetence! There might be differences in competence between men and women that make a big difference to scientific productivity but are completely undetectable by academic testing and unmentionable by faculty! There might be really big differences that everyone conspires not to admit to the existence of! Sure, there might. And the earth might be 6000 years old.
Just that if you asked, ahead of time, a question like “So, what would it take to convince you beyond reasonable doubt that there’s bias favouring men over women in the academic employment market?”,
If this is indeed the case than why isn’t the system approaching an equilibrium similar to the one the system reached for Asians, Irish, and Scottish Highlanders?
I don’t think I can usefully attempt to answer the question, because it isn’t perfectly clear to me (1) what sort of “equilibrium” you have in mind or (2) why you think I should “if this is indeed the case” expect the system to approach such an equilibrium. The linked article, consisting mostly of several pages of Macaulay, doesn’t do much to make either of those things clear to me.
The point is that Asians, Irish, and Scottish Highlanders were able to overcome negative stereotypes and “microagressions”, and whatever other epicycles the SJW crowd feels like inventing, towards them. Why not blacks and women? You know maybe there really are innate differences involved here.
The question seems like it has a false premise, namely that women and black people haven’t made progress in overcoming those things. In fact the treatment of both groups has improved tremendously over, let’s say, the last 50 years. Which is roughly what we might expect if in fact much of the difference in how they’d been treated before was due to bias.
(It’s probably also what we’d expect if the difference was not due to bias and these groups gained in political power for some reason other than having their genuine merits recognized better. So I’m not claiming this as positive evidence for that bias. But your argument, if I’ve understood it right, is that the bias theory must be wrong because if it were right then the treatment of these groups would be improving—and in fact it is improving. I’m not aware of any reason to think it’s converged to its final state.)
In fact the treatment of both groups has improved tremendously over, let’s say, the last 50 years.
I agree the “treatment” has improved. They still can’t make it in intellectually demanding occupations except by affirmative action. Let’s take the most technologically innovative part of the economy: Silicon Valley. Men massively outnumber women in technology jobs, as for race Blacks are massively underrepresented and Asians are massively overrepresented.
They still can’t make it in intellectually demanding occupations except by affirmative action.
To avoid begging the question, that should be “don’t”.
200 years ago it was basically unthinkable for most women to have any role other than parent and housekeeper. 50 years ago it was basically unthinkable for women to have senior leadership roles or to work in the most intellectually demanding jobs. Now it is thinkable but uncommon; at least some of them appear to do pretty well but they are few in number. Prima facie, the continuing underrepresentation could be because of differences in ability distribution or personality traits or sometihng; or because of (reduced but still remaining) prejudice; or some mixture of both.
Your argument a couple of posts back, if I understand it right, was: It must be because of differences in ability, because otherwise they’d be doing OK now just like East Asians are. So far as I can see, that argument only works if there’s some reason to think that if the past shortage of women in those roles were the result of prejudice, then by now it would be completely repaired. But I see no reason to expect that; prejudices can last a very long time. It looks to me (though I don’t have statistics; do you?) as if the current rate of change in women’s career prospects is still substantial, suggesting that if the last few decades’ changes are the result of prejudice reduction then the process isn’t yet complete and we shouldn’t assume that we are now at the endpoint of the process.
Note also that there were no people tacking about “microagressions” or for that matter much in the way of affirmative action when these groups succeeded.
That language seems to presuppose that whatever change they achieved has now stopped. As I said above, I think that’s very far from clear.
the closing of the gender gap appears to have stopped
That post seems long on anecdote and short on data.
Pages 10-11 of this document seems to show a steady decline in full-time gender pay gap from 1970 to 2010. The part-time figures are weirdly different; by eye they seem to show one downward jump circa 1974, then approximate stasis, then another downward jump circa 2005.
What it would take to show that there is bias favoring men over women would involve showing that men are more likely to be hred than women and that this imbalance in hiring rate is not justified.
It seems to me that for that to be so, there would need to be absolutely huge differences between men and women, so big that no one with any brain and any integrity would deny that men are much much much better scientists than women.
If you apply a high cutoff the difference is pretty big.
In the present case—as you would see if you looked at the study in question, which I therefore guess you haven’t—the level of ability we’re looking at (for “male” and “female” candidates) is not super-high, and in particular isn’t high enough for the sort of variance difference you have in mind to make a big difference.
These are candidates with a bachelor’s degree only, GPA of 3.2, and all the information in the application designed to make them look like decent but not stellar candidates for the job. We’re not talking about the extreme tails of the ability distribution here; the tails have already been cut off.
All the listed information is actually remarkable little. Like I said below the most “objective” thing on your list is the GRE score and even standardized test scores have high variance.
when everything about the applications was exactly the same apart from the name.
Would that “everything” include things like college degrees, remember affirmative action is a thing in college admissions. Also, an applicant’s sex conveys information, are you sure the other information was enough to completely screen that out? The other thing to take into account is that if I hire a women and she doesn’t work out, I risk getting hit with a wrongful termination suite if I fire her.
They took the exact same application, sometimes with male-looking names and sometimes with female-looking names, and asked faculty for their opinions about them. The female versions were rated substantially (and significantly at the 0.001 level) worse for “competence”, “hireability” and “willingness to mentor this student”. The gap in estimated competence was about the same in size and significance as the gaps in the other metrics, which to me seems to indicate that differences in fear of a wrongful termination suit didn’t contribute much if at all. (On looking at the relevant bit of the paper, the authors agree and have some statistical analysis that allegedly supports this view.)
When asked roughly what starting salary they’d offer the applicants, the “female” applications attracted ~12% lower figures.
(The details are all there at the other end of the link I gave.)
are you sure the other information was enough to completely screen that out?
I’m not completely sure of anything, ever. But: The information included: age, degree granted and university that granted it, GPA, GRE scores, extracts from application letter and faculty letters of recommendation, etc. If there’s any residual information to speak of in knowing whether the applicant was male or female, I’d be rather surprised; if there’s enough to justify the differences found in the study, I’d be flabbergasted.
[EDITED to add: While affirmative action may be “a thing in college admissions”, to the best of my knowledge it is not “a thing” in the awarding of college degrees, the calculation of GPAs, etc.]
If women are more likely to use maternity leave or otherwise devote more resources to family and less to the job than men are, and if they are more likely to sue for sexual harassment than men, then most of these assessments could be correct; seeing a female name actually does give information.
As I have said a few times already in this thread, the numbers make it look very much as if the dominating factor was an assessment that the “female” candidates were less competent than the “male” ones. Lack of commitment and increased lawsuit risk don’t seem to me like matters of competence and I would expect the faculty surveyed to share that opinion.
Do you have a rough estimate of (1) how much more likely women would have to be than men to do those things, in order to justify a difference in evaluation of the magnitude found by this study, and (2) how much more likely women actually are to do those things?
(Two remarks in regard to sexual harassment lawsuits. 1: I think the relevant figure isn’t how much more likely women are to file such suits but how much more likely they are to file them when no harassment has really occurred. But perhaps not: suppose women are more likely to be victims of sexual harassment sufficient to justify a lawsuit, and therefore more likely to file such lawsuits; then one possible position would be to consider women less desirable employees on those grounds and rate them as less competent. Personally, I think that would be odious, but I can imagine that some people might disagree. 2: My understanding is that actually such lawsuits are really rather rare, much too rare for rational consideration of their risk to yield the reported difference in evaluation even if (a) all such lawsuits are assumed groundless but successful and (b) the resulting losses in productivity and collegiality are assigned to lack of “competence” by the person filing the lawsuit. However, I don’t have extensive statistics on this and will be happy to be corrected if wrong.)
I think the relevant figure isn’t how much more likely women are to file such suits but how much more likely they are to file them when no harassment has really occurred.
The problem is that “whether sexual harassment has occurred” isn’t all that well-defined. You can of course define “sexual harassment” however you want but then you have to establish you it’s a bad thing. For example, from a briefing at the company I work at the examples of “sexual harassment” was:
1) a woman goes to work in somewhat provocative/revealing clothing and a male coworker complements her on her appearance.
2) a manager used the phrase “guys and gals”.
Frankly if these examples are typical of “sexual harassment”, I’d say sexual harassment isn’t a problem.
I don’t know, the presenter didn’t say. Although the fact that these were presented as examples of behaviors not to engage in, is telling. Also even if they don’t bring a lawsuit, the fact that they make an issue out of these kinds of things is not conducive to a good work environment.
Of course I wasn’t there. But it occurs to me that there are several reasons why “marginal” examples might actually be the most useful:
To define the region of (concept-)space a thing occupies, you might want to point to a few places on its boundary.
There’s little point telling people “raping your co-workers is bad; don’t do it” because anyone to whom that isn’t already obvious is probably a lost cause.
Marginal examples might be more likely to provoke useful discussion.
I’d put the examples you give in the category of (not typical examples of sexual harassment, but) things that are frequently harmless but (1) might cause easily-avoided annoyance or upset in some cases and so should maybe be avoided and (2) in some cases might indicate, or be thought to indicate, an underlying bad attitude (women in the workplace being seen primarily as eye candy; women being seen as lower-status and akin to children).
I repeat: of course I wasn’t there and don’t know exactly what your presenter said about these examples. If s/he said “these things are definitely harassment and you could get in serious trouble for doing them” then I’d regard that as unreasonable; if s/he said “these things may seem harmless, and often they are, but you should still avoid them”, I’d agree.
Anyway, I mention all this just in the interests of mutual understanding; it’s all kinda irrelevant to the question of whether “greater risk of sexual harassment lawsuits” is a good justification for rating an identically-described person as substantially more “competent” if they have a male name than a female name. Do you really think it is?
To define the region of (concept-)space a thing occupies, you might want to point to a few places on its boundary.
The problem is that it causes people to treat it as an archetypical example.
I’d put the examples you give in the category of (not typical examples of sexual harassment, but) things that are frequently harmless but (1) might cause easily-avoided annoyance or upset in some cases and so should maybe be avoided
I fail to see why it should be policy to cater to people who are clearly being unreasonable.
I fail to see why it should be policy to cater to people who are clearly being unreasonable.
For one thing, because being unreasonable is simply What People Do and it seems better to care about outcomes in the real world than outcomes in some imaginary world where everyone is always reasonable. So if doing something predictably results in a bunch of people being upset, then it might be better to avoid it even if it would be better for everyone if they weren’t upset by it.
For another, because what’s “clearly unreasonable” to one person may be “clearly reasonable” to another. It may seem “clearly unreasonable” for a woman to have a problem with having her appearance complimented by her male colleagues. But if what she’s found is that over and over again her male colleagues comment on her (and other women’s) appearance, and never on their ideas, while the reverse happens to the men around her … why, then, I have some sympathy if she gets frustrated by yet another compliment on her appearance. (It might in some sense be better for her to focus not on the compliments on her appearance but on the absence of response to her work. But actual things that actually happen are easier to see and more psychologically salient than absences, even when the absence is the bigger underlying problem.)
The problem is that it causes people to treat it as an archetypical example.
Only people who are—how shall I put it? -- clearly being unreasonable. One might prefer not to make policy on the basis of people who are clearly being unreasonable :-).
Seriously: yes, I agree that that’s a potential problem. The obvious solution seems to me to be to make it as clear as you possibly can when you’re talking about central examples and when you’re sketching the boundaries. Unfortunately, I bet there will always be (clearly unreasonable) people who don’t take any notice and either mix the two up or pretend to. I’m not sure much can be done about that.
But if what she’s found is that over and over again her male colleagues comment on her (and other women’s) appearance
Well, complimenting people wearing attractive clothes is is simply What People Do and it seems better to care about outcomes in the real world than outcomes in some imaginary world where no-one ever notices other people’s clothes. So if wearing certain clothes predictably results in a bunch of people commenting on your appearance (and it annoys you), then it might be better to wear more modest clothes yadda yadda yadda.
You say that like you expect me to disagree, but I don’t think I do. (But I would generally avoid saying so to the people in question, which I might not on the other side, because it seems more obviously unreasonable to have to avoid wearing nice clothes to work than to have to avoid complimenting people’s clothing at work. I’m not terribly sure how much sense that makes, though.)
But I would generally avoid saying so to the people in question, which I might not on the other side, because it seems more obviously unreasonable to have to avoid wearing nice clothes to work than to have to avoid complimenting people’s clothing at work.
It seems even more unreasonable to be to wear sexy clothes (how did “sexy” turn into “nice”?) and then object when someone comments on them. Frankly the only way I can explain the woman’s actions are that she was either insulted that the complementer was too low status or trolling for an excuse to accuse someone of sexual harassment.
I don’t think it did, exactly. I just didn’t assume that clothes that could be described as “somewhat provocative/revealing” necessarily belonged in the bucket labelled “sexy” rather than the one labelled “nice”.
To be more precise: (1) what is viewed as provocative or revealing is highly dependent on who’s doing the viewing (see, e.g., Victorian England or many Muslim-dominated places today; but similar variation occurs at the individual as well as the societal level), and (2) person A may wear clothes that person B finds “revealing” without the least intention of attracting sexual attention of any sort.
I have no quantitative data (and doubt whether any exist) but have more than once heard women complain that their choice of clothing was treated by a man as some sort of attempt to provoke when in fact they were just wearing something they felt comfortable in or liked the look of. (I have a feeling there is pretty decent scientific evidence that men tend to overestimate the extent to which women’s behaviour is intended to signal sexual availability or interest, but don’t have references to hand. It seems like a plausible hypothesis on the usual handwavy evo-psych grounds, for what little that’s worth.)
I don’t know what she was wearing, I heard it from the lawyer doing the briefing, but he did mention her undoing some buttons. In any case, if I came to work wearing a suite, we dress casually, I’d expect people to comment on it.
I was about to go ‘sweatshirts for example are comfortable but definitely not provocative’, then I remembered reading that when men talk about comfortable clothes they tend to mean physically comfortable whereas women tend to mean socially/psychologically comfortable (as in this comment, though I don’t know if Nornagest is a woman).
(Then again, being comfortable in the latter sense with wearing certain clothes but not with being complimented for them sounds weird to me.)
Sure. It sounds a bit weird to me too, for what it’s worth. But the whole point here is that the reasons why something is unpleasant to one person may be far from apparent to another. Anecdotally, it seems that many women have the experience of being persistently treated (so to speak) as ornamental rather than functional, of having their male colleagues pay attention to their appearance while neglecting their work. Someone in that situation may not be glad of compliments to her appearance even if she has gone to some trouble to look good.
An analogy occurs to me. Let’s suppose that an important part of your employment is writing analytical reports of some kind. Stock market forecasts, competitive analysis of other companies’ products, software requirements, that sort of thing. You write these reports. You hand them over to your boss. And he takes a look and says “Nice choice of font.” or “I see you spelled ‘accommodate’ correctly, well done.” A single instance of this is harmless and you’d probably be glad of it. But it happens again and again, much more often than any substantive comment (positive or negative) on the actual content of the reports you’re writing. After a while, you might start taking these comments as indicating that your boss either thinks the content is no good, or for some reason simply doesn’t much care about the content. You might find that being complimented on your excellent use of quotation marks makes you feel bad, not good, about how valuable your carefully calculated and checked risk assessment is to the company.
And you might feel that way even if, as a matter of fact, you did put some care and skill into spelling and punctuating correctly and presenting the report attractively.
Sure. It sounds a bit weird to me too, for what it’s worth. But the whole point here is that the reasons why something is unpleasant to one person may be far from apparent to another.
Now who’s making highly implausible theories and arguing that they’re “possible”?
You write these reports. You hand them over to your boss. And he takes a look and says “Nice choice of font.”
Well, if I had made an unusual choice of font, I’d expect that reaction.
It doesn’t appear to me to be a highly implausible theory; it’s a thing many women actually complain about.
Well, if I had made an unusual choice of font
My understanding is that quite a few women report male attention going disproportionately to their clothes and appearance even when they aren’t wearing anything very unusual.
Also, there are other employees around who are proud of their use of quotation marks and specifically expect that they be complimented on them. Some of them even leave reports on their desks with pages of words prominently displayed just so that people will compliment them on their punctuation.
And there are even more employees who really want to be complimented on their use of quotation marks, but only from people with small noses. This unusual preference is something they don’t want to admit, so these other employees, when complimented by someone with a big nose, pretend to be like you and be offended because they are not being complimented on content, when that’s not true at all.
I think in an environment like that you should expect to get complimented on your punctuation quite a bit.
The problem with compliments isn’t so much that woman often don’t enjoy getting them. There are many cases where they don’t, but that’s not the central issue.
The problem is that it’s hard for a man to compliment a woman on her appearance and at the same time not let it influence how he treats the woman in their professional function. The availability heuristic is a central part of how humans make decisions and if the attribute that most available is “attractive” instead of “skilled-at-job” that matters.
The availability heuristic is a central part of how humans make decisions and if the attribute that most available is “attractive” instead of “skilled-at-job” that matters.
The problem with the problem is that not everyone actually means that. And the ones who don’t mean it end up reducing the credibility of the people who say it and really mean it.
Also, there are other employees around who are proud of their use of quotation marks and specifically expect that they be complimented on them.
Sure. But after a couple times I compliment on your punctuation and you don’t take it well, I should get the hint and realize that you aren’t one of those people. (And whether you do like to be complimented on punctuation by people with smaller noses¹ than mine is irrelevant; if you don’t like it when I do it, I should stop it, at least until I can afford a rhinoplasty.)
Some of them even leave reports on their desks with pages of words prominently displayed just so that people will compliment them on their punctuation.
I was about to go ‘but there’s a large difference between writing in a formal standard grammatically correct way and writing in a way that fishes for compliments!’, then I remembered that that’s probably much less the case in the America than where I am (see e.g. [1], [2]; by comparison where I am you can just wear canvas sneakers or tennis shoes, jeans, and a T-shirt or a sweater, and that’s not necessarily considered sexy but not necessarily slovenly either, regardless of your gender), so never mind.
“Native speakers” would be a less silly allegory, BTW.
And whether you do like to be complimented on punctuation by people with smaller noses than mine is irrelevant; if you don’t like it when I do it, I should stop it,
Using your analogy of native speakers, people want to be complimented on their punctuation by native speakers only. When complimented by anyone who doesn’t speak well enough, they lie and say “I don’t like it because you’re not complimenting me on the quality of my work”, when they’re really just using it as a cover for an implied insult of “I hate people with your accent”. This proceeds to the point where everyone knows that the former complaint is just an excuse for the latter.
Then you come along, and you really want to be complimented on the quality of your work. You’re going to be mistaken for those other guys quite a bit.
Doesn’t change my point. If you are predictably annoyed when I compliment on your punctuation and I know it, I’d better stop it if I don’t want to be a dick, regardless of why it annoys you.
I don’t believe that. For instance, if you are white, I am not, and you are offended by compliments because you are offended whenever a non-white person talks to you or even sit next to you, it’s not me that’s being a dick by offending you, it’s you who’s being one by being offended by things that you have no right to be offended by.
That’s essentially what’s going on here—some people who are offended are offended for a reason that doesn’t deserve to be respected (they dont like someone’s accent/they don’t want to be complimented by someone low status), and they lie and pretend they are offended for a reason that does deserve to be respected (they don’t want shallow compliments).
Not wanting to be complimented for being sexy by unsexy people doesn’t deserve to be respected? WTF? Would you be okay with it if someone you’re not only not attracted to in the slightest but perhaps even repulsed by said something to the effect that they would like to bang you (even though not with those words)?
I might want to restrict such things to being said only by someone who I’m in a relationship with, but that’s different from restricting such things to only being said by all beautiful people.
This proceeds to the point where everyone knows that the former complaint is just an excuse for the latter.
Then it’s not a lie. That’s not how natural languages work. If everybody knows that when people say X they mean Y, then X means Y, regardless of etymology. There’s no stone tablet in the sky that specifies what X actually means regardless of when people actually say X and when they don’t. (Or would you say that someone saying “it’s raining cats and dogs” in absence of domestic carnivorans falling down from clouds is lying?)
And if of the possible ways of wording a complaint someone chooses the one least likely to hurt my feelings, why should I hold it against them, rather than being grateful for that?
If everybody knows that when people say X they mean Y, then X means Y, regardless of etymology.
Hold on. I’m not arguing that X doesn’t mean Y. I’m arguing that X does mean Y, and that explains why people treat Y as X. (X=I don’t want to be complimented by ugly/low status people, Y=I don’t want to be complimented based on superficial attributes, by anyone).
when men talk about comfortable clothes they tend to mean physically comfortable whereas women tend to mean socially/psychologically comfortable (as in this comment, though I don’t know if Nornagest is a woman).
I meant “comfortable” as an attribute of the social situation in that comment, not of the clothes I’d be wearing in it. If I were wearing sweatpants to a wedding, for example, I’d likely find them comfortable but I wouldn’t be comfortable.
I thought that was what I was suggesting is best—at least if it happens that the women in question can actually avoid having the men focus on their appearance by making changes in clothing. I can’t help suspecting (though I have no actual evidence) that in such cases their options are actually “get unwanted compliments from men who focus on their appearance and ignore their ideas” and “get unwanted critical comments from men who focus on their appearance and ignore their ideas”, with perhaps a little middle ground where they get both positive and negative comments on their appearance and still have their work overlooked.
While lawsuits may be rare, they are expensive, and people are risk-averse.
Also, the range of behavior that has to be avoided to avoid an unjustified lawsuit is much wider than the range of behavior that has to be avoided to avoid a justified lawsuit, and since even unjustified lawsuits are expensive, the former category is what really matters.
Your second paragraph seems to be agreeing with the first of my parenthetical points, but it sounds as if it’s intended to be a point of disagreement. I mention this just in case it turns out that one of us has misunderstood the other.
Unjustified lawsuits are probably cheaper—you’re more likely to win them, more likely to win them quickly, and more likely (in jurisdictions where this is a real distinction) to have the plaintiff have to pay your legal costs.
Your second paragraph seems to be agreeing with the first of my parenthetical points, but it sounds as if it’s intended to be a point of disagreement.
It was disagreeing with your second point, “much too rare for rational consideration of their risk to yield the reported difference in evaluation”. If the person is risk-averse, then it’s not too rare for rational consideration of the risk to yield the difference. (Don’t assume that risk aversion is inherently iirational. It’s not.)
I don’t understand. It was your first paragraph that was pointing out risk aversion. The second paragraph was the one about unjustified versus justified lawsuits. (Let me try to bridge one possible inferential gap by remarking that I think unjustified sexual harassment lawsuits are also very rare.)
So is your claim that the scores on a single GRE test completely capture everything about an applicant relevant to job performance?
I find your question absolutely bewildering, given that the very sentence I wrote that mentioned GRE scores mentioned them only as part of a list of things.
Yes and when I pointed out the problems with all the other things in the list your reply basically amounted to “you haven’t made any objections to GRE scores”.
You didn’t point out the problems with all the other things in the list, you made a claim about one thing in the list. My reply did not (as I have already pointed out) amount to “you haven’t made any objections to GRE scores”.
Regardless, no metric is perfect, and no one has been claiming otherwise. Accordingly, it is possible in principle (as I have already said more than once in this discussion) that there might be male/female differences that are either really huge, or highly relevant to scientific competence but startlingly uncorrelated with all the information provided to the faculty in this study, and that render the assessments they made rational given the information they had.
However, it seems pretty unlikely to me.
What do you think? Is the best explanation for these very different assessment of identical applications from differently-named candidates, in your opinion, that the faculty making the assessment are aware of such huge differences between men and women and have weighed them roughly correctly (not necessarily consciously and explicitly) to arrive at the results that have? If so, could you sketch for me roughly what these differences are and how they lead to that result? Because I’m having real trouble thinking of any hypothesis of this sort that’s consistent with what I think I’ve observed of the relative abilities of men and women.
Accordingly, it is possible in principle (as I have already said more than once in this discussion) that there might be male/female differences that are either really huge, or highly relevant to scientific competence but startlingly uncorrelated with all the information provided to the faculty in this study
Do I believe that Americans are generally more intelligent than Europeans? No, I don’t. At the same time in the LW census the average American has somthing like a 10 point higher IQ. In the data set there a strong correlation.
I think the intuition that the factor of the name should be zero is wrong even if there no causal effect because gender simply interacts in complex ways with many other things. I’m not sure in what direction the factor is going to correct, which might also be different in different situations but assuming that it contains no information at all doesn’t seem to be right.
I just grabbed the latest LW survey data I could find, selected (1) rows with “United States” as country and something other than a null for IQ and (2) all rows with something other than a null for IQ. (Note that this doesn’t include any sort of selection on the basis of reliability of IQ score.) I got means of 138.3 for the larger dataset (472 numbers, stddev=13.6) and 140.7 for the smaller (249 numbers, stddev=13.5). I wouldn’t call that “something like a 10 point higher IQ”.
the intuition that the factor of the name should be zero
What intuition that it should be zero? The question is whether it should be very large, not whether it should be exactly zero.
I’ve already explained why the difference would need to be very large for these results to be correctly explained by saying that the rating faculty made accurate allowance for real male/female competence differences. If you missed that, or you think I got it wrong, or it didn’t make sense, do let me know.
If so, could you sketch for me roughly what these differences are and how they lead to that result?
Let’s see: there are numerous ones the most relevant are: women have less variation in intelligence then men and so there fewer unusually smart women. Women are worse at taking criticism. There is also a lot of stuff about the kind of hierarchies men and women tend to form.
Because I’m having real trouble thinking of any hypothesis of this sort that’s consistent with what I think I’ve observed of the relative abilities of men and women.
Have you actually been observing the relative abilities between men and women, or is your reaction whenever you notice a woman doing something badly or acting emotionally to hit yourself for having a “sexist” thought?
women have less variation in intelligence than men
That could indeed (if the numbers work out) explain a difference in success at the very highest levels in the absence of prejudice. But this sort of effect is far weaker away from the very tails of the distribution, and the particular study we’re taking as an example in this discussion is not concerned with the very tails of the distribution. Further, my understanding is that GRE scores correlate somewhat better with intelligence than they do with job performance (see, e.g., this post which has a few references to the primary literature), and I would expect them to do a pretty good job of screening off differences in raw intelligence in this case.
Women are worse at taking criticism.
Evidence? (I have to say it looks to me as if people are bad at taking criticism, and I haven’t noticed a big difference between men and women; but I’ve not studied this and will be glad to learn.)
a lot of stuff about the kind of hierarchies men and women tend to form.
I’m afraid that’s not specific enough for me to form any idea of how it would justify a drastically lower assessment of the likely competence of a woman than an identically-credentialed man as a scientific lab manager.
Have you actually been observing the relative abilities
Relative abilities as such are pretty much unobservable. I’ve been observing the relative performance. But only casually and qualitatively; if you have a pile of useful data then by all means point me at it.
is your reaction [...] to hit yourself for having a “sexist” thought?
No, not at all. I notice both men and women doing things badly and acting emotionally all the time, and feel no particular impulse to self-punishment when I do so. -- Is it your usual practice to assume that people who disagree with you are off their heads, or have I said something to give you that impression particularly strongly in my case?
(Note for the avoidance of doubt: I am assuming that you didn’t mean “hit yourself” literally; of course if you did then it’s an even weirder thing to think I might do.)
My understanding is that the correlations in question persist, and are not small, when those other things are either controlled for or taken out of the picture. For example, here is an informal writeup of a PNAS article finding evidence of bias favouring male over female job applicants when everything about the applications was exactly the same apart from the name.
There are even clearer examples of gender bias on the unconscious level. The fact that women are hired at equal rates as men by orchestras if, and only if, the audition is behind a curtain and everyone enters barefoot so the hiring committee cant tell gender by footstep sounds is the most damning I can think of right now. Because that is a straight up test of competence at the only skill relevant for the job, and applicant genitalia still sway supposed experts unless extreme measures are taken to blind them to that factor. Basically, at this point there is such a huge pile of evidence that human beings are just completely incompetent at screening out utterly irrelevant factors that I would judge it sensible hiring policy in any field to have the job interview behind a curtain and a vocoder.
… Fuck it, I’m using that in a story. It fits right into a certain culture I’m building. ;)
I would not recommend conducting hiring tests for an orchestra behind a vocoder :-).
(Other than that: yes, I agree, except that actually conducting hiring interviews that way would probably actually lose more signal than it eliminated noise, at least in the fields I’m familiar with interviewing in. Alas.)
Just curious… What fields are those?
Software development, engineering, mathematics (in industry rather than academia).
The loss of signal could probably be eliminated in all of these, with some effort. The sort of thing I’m thinking of where signal would be lost by default is where you ask the interview candidate to design something, write a bit of code, sketch a system they worked on in the past, etc., on paper or whiteboard. If the candidate has to be behind a curtain, that’s difficult to do and probably involves irksome extra latency (e.g., a system where they write or sketch whatever they want to and then step aside, and only then does the interviewer get to see what they did).
You could work around this with computerized whiteboards—the candidate sits in one room and the interviewers in another, both rooms have electronic whiteboards, and they are coupled so that anything written on one shows up on the other too.
(Or by using something other than whiteboards that’s easier to decouple in this way. For instance, for a coding task some kind of collaborative text editor may do better.)
I see. (I had guessed you were talking of people who have to directly¹ interact with perspective customers, so you have to know what they look and sound like in order to know what first impression perspective customers might get.)
Of course what “directly” means depends on where you are; I hear there’s a country where people will boycott a Web browser solely because of the political stance of the CEO of the company making it on a topic with hardly anything to do with software. ;-)
Yes, that would be another example. But, I think, a different sort of example. Let’s suppose that candidate A comes across better than candidate B in interview simply because of widely-shared prejudices affecting the interviewers. For the kind of job you describe, that (rather horribly) means that candidate A probably is better able to do the job than candidate B.
(It might well be that the best thing overall is to try to stop people in that situation favouring A over B on account of prejudice anyway, in the hope that over time this reduces the overall level of prejudice and everyone is better off.)
Does that include e.g. the likelihood of the applicant going on maternity leave in the near future?
There is a really nifty way to solve this, by the way. Do what the Norwegians do. Half of maternity leave accrue to the other parent and is non-transferable.
That way career impact of child birth becomes gender neutral—for anyone married, anyways. And like all the best of feminist ideas, it is irreversible policy because it benefits both genders.
Men get time of to spend some time with their kid, and women don’t have to worry about potential employers shunning them out of fear of having them go on leave because potential employers cannot hire anyone without that risk attached. Well, post menopausal women, I suppose. Doesn’t seem likely to become a dominant hiring strategy.
Of course, maternity leave isn’t the only way in which women can chose family over career. Also, this kind of policy amounts to valuing “equality” for its own sake above everything else, like productivity.
.. Norway has labor productivity 35 percent higher per hour worked than the us does. They work a bit less, so the country as a whole is only 27% percent richer than the US is. Yhea, this is really a policy that dings economic productivity.
Also, basic logic: What is the contribution to the formal economy of a woman who can’t find work due to gender discrimination?
Sigh. Do you bother to check your numbers?
In 2013 the productivity in Norway was 62.6 GDP/hour while in the US it was 57.5 GDP/hour (source). And I bet that’s the consequence of the fact that a large part of Norway’s economy is offshore oil and gas which are highly capital intensive and so generate very high productivity.
Note that in Sweden, a country with social policies broadly similar to Norway’s but without the oil, the productivity is 45.0 which is noticeably lower than in the US and is close to the EU average.
The country as a whole is much poorer that the US because it is much smaller. I suspect you meant things like GDP per capita which for Norway is indeed higher that for the US (again, because Norway has a small population and pumps a lot of oil out of the North Sea).
I was using the OECD databases, except I was not using 2005 PPP to compare 2013 gdp. Which is what is in your link. Setting the exact same table to compare against the US as the hundred percent baseline gives a number for Norway of 130.2 Which isn’t what I got from the table I was using, so obviously the OECD doesn’t agree with itself at all times o,O Oh well.
Further checking the OECD quickly, no, the lead isn’t down to petroleum alone—absurdly high in all sectors, save agriculture. Which is mostly down to Norway being an idiotic place to grow crops. And that lead is growing, so it is not a legacy—their current policies are successes.
If oil has anything to do with it I strongly suspect that it is via indirect political effects—No Norvegian politician can implement austerity or embark on a campaign to suppress wage growth due to the oil money, so the country doesn’t shoot it’s own economy in the knee on a regular basis like the rest of the west does.
But never mind statistics. Do you have issues with the basic logic? “Policies that remove gender based barriers to employment are good for the economy, due to the basic fact of life that housewife is a ludicrously low-productivity job sector”. Heck, near as I can tell, a good chunk of the wealth gain’s of the past 50 years has mostly been the working out of the productivity implications of household appliances − 2 income households are possible because the electric stove, the refrigerator and the vaccum means keeping house isn’t a full time job.
Re: Being poorer than the US due to smaller size. That isn’t how people use the word rich. Depending on which statistics you use, China has an economy which either is, or will shortly be, larger than the US one. Would you consider it reasonable to refer to China as richer than the USA once that absolute size becomes indisputable?
What do you mean “remove gender barriers”? Do you mean policies requiring companies to hire be “non-sexist” in their hiring practices etc.? Because if those practices increased productivity companies would use them anyway.
Also have both spouses work tends to result in the couple having a lot fewer children. In fact in another thread people were complaining that they couldn’t afford to have kids because they couldn’t subsist on one income.
I am sure they can subsist on one income, it’s just that they don’t want to.
I don’t think that distinction matters much to the point Azathoth123 is making. (Personally I’d put the family in that thread in the grey area between “couldn’t subsist on one income” and “maybe could but it would be terrible”. Husband and wife on $10k/year each. I wouldn’t want to try supporting a family of three on $10k/year, though maybe it could be done if “supporting” means “living on the streets and barely managing to feed” or “scraping by using every bit of government-supplied assistance available”.)
I wouldn’t want to support a family of one on $10K/year. But I think the context of this discussion is that the middle class feels the need for two incomes and so the wife works instead of being a housewife.
Unless there’s some kind of PD-like situation whereby sexist hiring practices benefit your company to the expense of everyone else’s.
I wasn’t aware that all firms are 100% rational and efficient. What causes them to fail, IYO?
Hurrah! Just what is needed in a world of over 7 billion people.
Link to numbers, please..?
I am sorry, I’m going to mind statistics. You seem to like numbers when they support (or can be made to support) your predefined conclusion, but when it turns out your statistics are wrong or misleading you go “never mind”.
Yes, because you can’t run a cost-benefit analysis without looking at costs.
That is how people use the expression “country as a whole”.
Is a ton of air as a whole denser than a gram of gold as a whole? IOW intensive quantities are intensive.
Is “rich” an intensive quantity, like “dense”, or an extensive one, like “heavy”? Meh. I’d say it depends on the context, and in the context of Izeinwinter’s comment I’d say it is clear which they meant.
And single men.
Because an unspoken condition of employment that prospective employees must stay single is a management technique made of win.
Errh.. Not. Good lord. would you want to manage a team made up of 100% celibate men? This is not a weakspot in the law, because it’s not a runaround anyone sane enough to not already be bankrupt would attempt.
It might on the margin inspire people to hire more people in their forties and fifties, - people who have had any children they are likely to have, but from the point of view of the government, that’s also not a flaw, but more of a “Secondary benefit free with just legislation”.
They make awesome startups. Redirected sexual energy is powerful :-)
Erm … there’s this guy in Rome who tried that … I think they had some problems.
Well the institution in question is the oldest continuously operating institution around today so they certainly have something going for them.
With chastity pledge as a part of the job contract.
Obviously not. Equally obviously, said likelihood has no bearing on the applicant’s competence, which was rated substantially and significantly lower by the faculty in the study when the application bore a female rather than a male name.
(Good statistics on this seem hard to come by, but it looks like the average age at first birth for college graduates in the US is about 30 nowadays; I’d say the probability of an imminent maternity leave for a 22-year-old with a new job as a lab manager in a university is pretty damn small, even if she happens to be called Jennifer rather than John.)
Competence in research might mean: “Likelihood that this person has the chance of making a valuable contribution to their scientific field.”
I don’t think that there anything wrong when a science faculty defines competence that way.
I’m too lazy to search for data on education-based cohorts, but only 57.5% of US women are childless by the age of 25.
The source I found showed a really drastic difference between college-educated and not-college-educated women.
That’s not necessarily irrational in general. The other information on the resume does not prevent the name from also providing potentially relevant information.
I’d suggest you look up “screening off” in any text on Bayesian inference. The explanation on the wiki is not really the greatest.
But when you have information that is closer and more specific to the property you’re trying to predict, you should expect to increasingly disregard information that is further from it. Even if your prior asserts that sex predicts competence, when you have more direct measures of competence of a particular candidate, they should screen off the less-direct one in your prior.
If there evidence that the effect size of discrimination stays the same regardless how much information an application provides?
I know what screening off is—I was saying that not all the information is screened off here. There are still other issues given the premise that names taken alone predict competence to some extent. For example, one resume may be more likely to be honest than another, and even if the resume is completely honest, reversion to the mean is likely to be larger in one case than another.
So: take a look at the paper, or at the informal summary of it to which I also linked, and then tell us whether you consider that—given all the information provided to the faculty in the application—knowing whether the candidate is male or female gives anywhere near enough further information to justify the differences in rated competence found by the researchers.
It seems to me that for that to be so, there would need to be absolutely huge differences between men and women, so big that no one with any brain and any integrity would deny that men are much much much better scientists than women. Do you think that’s the case?
I think that regardless of the actual facts, assuming the difference is counterfactually that large, it’s still very plausible that almost everyone would still deny any difference exists, due to political and cultural forces.
While I don’t think there is such a large difference, I don’t accept the argument from “people wouldn’t pretend a big difference doesn’t exist”.
I wasn’t merely arguing that if there were such a large difference everyone would admit it. I was also arguing that if there were such a large difference we’d all know it. Obviously this argument will be more persuasive to people who (like me) think it’s clear from observation that there isn’t so huge a difference between men and women, than to people who don’t.
Just by way of reminder: we’d be looking for a difference large enough that, knowing
what degree a person got from what institution
what their grade point average was
what their GRE scores are
what was written about them by a faculty member writing a letter of recommendation
what they wrote themselves in an application letter
the difference between male and female suffices to make a difference to their estimated competence of 0.7 points on a 5-point scale. That would have to be either a really really enormous difference between men and women, or a really weird difference—weird in that whatever it is somehow manages to make a big difference in competence without having any effect on academic performance, test scores, or reported faculty opinions. Which presumably would require it to be quite narrow in scope but, again, really really enormous in size.
And it seems about as obvious to me that there isn’t such a difference as that (say) there isn’t a difference of 20cm in typical heights between men and women. Not just because if there were then it would be widely admitted (maybe it would, maybe not) but because it would be obvious.
Now, of course I could be wrong. There could be such an enormous difference and I could be somehow blind to it for some weird cultural-political reason or something. But is it really too much to suggest that when
the exact same job application gets radically different evaluations depending on whether the candidate’s name is “John” or “Jennifer”
it’s reasonable to take that as strong evidence for bias in favour of men over women that isn’t simply a proportionate response to actual differences in competence? I mean, it’s just Bayes’ theorem. How likely is that outcome if people do have such bias? How likely is it if they don’t? (Not “is it possible if they don’t?”. The answer to that sort of question is almost always yes, regardless of what’s true.)
It’s not entirely clear that these are two different things. Admitting a highly politically incorrect opinion publicly and admitting it to oneself or one’s friends aren’t really completely separate. People tend to believe what they profess, and what they hear others profess.
I suspect one source of the disagreement between us may be that you’re assigning a high predictive ability to academic performance, while I don’t even assign it a very high correlation. This may be because my intuition is trained on different academic fields. I don’t have any experience with scientific lab managers (the job the study’s resumes applied for). I do have experience with programmers and other related fields, mostly below the doctoral level.
When I first read that I thought: but there is about a 20cm difference in the average heights of men and women! Is gjm arguing the opposite point from what I thought, or maybe being sarcastic?
So I checked the average height differences between the sexes, and the male:female ratio is typically between 1.07-1.09. This translates to 8-15 cm of difference. So while it’s not as much as 20cm, it’s “only” a 2x difference from my prediction. Maybe I’m just bad at translating what I see into centimeters and this difference is much more obvious to you than it is to me.
I don’t disagree with this. I just think the cultural power of “politically correct” thinking is strong enough to make people ignore truths of the magnitude of this being counterfactually wrong and stick to accepted explanations.
Maybe gjm’s System 1 automatically compensates for the difference—I know that unless I’m deliberately paying attentìon to people’s height I’m much less likely to notice it if a man is six feet tall than if a woman is six feet tall, and for all we know the same might apply to gjm.
I’m guessing this effect doesn’t just apply to height.
Yeah, I know, people consider my barely basic¹ cooking skills exceptional merely because I happen to have a Y chromosome. That’s male privilege for ya.
At least that’s what my System 1 tells me, and I can’t think of a way to find out whether the impostor syndrome applies short of having someone who doesn’t know my gender taste what I cook.
Academic performance is one of the things known to the faculty (and the same between the “male” and “female” conditions); it is not the only one. The relevant question is: How much predictive power does the totality of the information provided have, and conditioned on that how much predictive power does the sex of the applicant have? It looks to me as if the answers, on any account of sex differences that I find credible, are “quite a bit” and “scarcely any”.
By “academic performance” I was referring to all of these bullet points:
Which (from your summary) I understand is pretty much all of the information in the application letter.
I’m not claiming that sex differences have predictive power; I’m claiming that academic performance doesn’t have as much power as we’d like and recruiters have to look for more info.
For sure. My apologies if I somehow gave the impression of disagreeing with that. The second half of what I called the “relevant question” above is of course the real key here, and it sounds as if maybe we agree about that.
No. If the argument is more clear because you think that it supports the outcome that you prefer you are engaging in motivated cognition. It’s an error in reasoning.
But I didn’t say, and I don’t think it’s true, that the argument is clearer “because [I] think it supports the outcome [I] prefer”. I “prefer” that outcome, in part, because it seems clear from observation that there isn’t that sort of huge difference between men and women. That is not a reasoning error, it’s straightforward inference.
So your theory is that all observed larger number of men at the upper end of any bell curve is due to sexism? And the larger number of men at the lower end of most bell curve, e.g., more men in prison is due to..something?
Most of the data I’ve seen suggests women have lower variance, here Robin Hansen discusses some of the implications about variance in test scores.
Nope. (What did I say to make you think that?)
My position is as follows.
There may well be differences in average performance between men and women in various intellectual tasks, in either direction. Indeed, there are some specific categories of tasks where the evidence for such differences seems strong; the most famous example is probably “mental rotation”. The difference for mental rotation is large but not enormous (about 1sd); my understanding is that all other sex differences found in scientific studies are smaller, and there are differences going in both directions.
It seems unlikely to me that there’s a big general cognitive deficit on either side. I believe girls are currently doing better than boys in pretty much all subjects at school in my country nowadays; in the past it was the other way around; so whatever differences there are (in this kind of task) must be smaller than the size of difference that can be induced by cultural effects. Of course this is consistent with deficits in very specific areas, with variance differences that affect how many really stellar performers there are of each sex, etc.
There may well be differences in variance between men and women. These differences might be fairly big, but it seems unlikely to me that they’re large enough to make huge differences at “ordinary” ability levels.
Once you start looking at the tails of the distributions, I expect them to be quite far from being Gaussian or even symmetrical. There are a lot more ways for things to go badly wrong than for them to go exceptionally right, after all. So I am skeptical about inferences from differences at the “low” end to differences at the “high” end.
There are certainly a lot more men than women in prison, especially if you look specifically at crimes of violence. However, lumping this together with variations in ability seems like a wilful embracing of the halo/horns effect; it seems like much of it will come from variations in sociopathy, enjoyment of violence, and other such characteristics that needn’t go along with worse performance as (say) a scientific lab manager.
For those last two reasons, any inference that looks much like “there are more men in prison, so we should expect more men to win Nobel prizes in physics” seems extremely suspect to me. Still more “there are more men in prison, so we should expect more men to make good lab managers”.
Putting all the above together: there may be well be differences in competence between men and women; they may well be bigger at the highest levels; I wouldn’t expect the differences to be enormous except maybe at the very highest levels where variance differences can be a really big deal.
All of that is independent from the question of whether there are sexist attitudes—by which, for present purpose, I mean: whether there are systematic biases that make men get evaluated better than women relative to their actual ability, likely performance, etc. Or, for that matter, worse.
It seems to me that there is a lot of evidence that there are such sexist attitudes, generally favouring men over women. We’ve had a lot of discussion of one study which seems to me like very strong evidence for such attitudes in one domain; I posted some links to some others. There’s a pile of anecdote too, but of course the way that looks may simply reflect what anecdotes I happen to have encountered. (I think the available anecdotage is at any rate evidence that sexist attitudes in both directions exist.)
The possibility of real ability differences has some bearing on how to interpret the apparent evidence for sexist attitudes, but in at least some cases—e.g., the study we’ve discussed so much here—it seems to me that it doesn’t make much difference, because to make the evidence not be strong evidence for sexist attitudes it would be necessary for the ability differences to be (what seems to me to be) unrealistically large.
The relevant question for most practical purposes is not the statistical difference between men and women in some particular kind of ability, but the statistical difference conditional on the information usually available when hiring (or when considering promotion, or when allocating places at a university, or whatever). Nothing I have seen so far gives me reason to think that these differences are large, even though the information in question is limited and unreliable.
(To get quantitative for a moment, let’s suppose everything in sight is normally distributed. Some underlying ability: male and female both have mean 0, but s.d. 1 for men and 0 for women. Some measure of ability equals the actual ability level plus noise with mean 0 and s.d. 1. Actual job performance looks like underlying ability plus other factors with mean 0 and s.d. 0.5. Then conditional on measured ability being +2 (i.e., well above average but not stratospheric), mean predicted job performance is about +1.0 for male applicants (with s.d. 0.87) and +0.8 for female applicants (with s.d. 0.80), a difference of about 0.2 (male) standard deviations. Definitely not zero, but not exactly huge either and a lot smaller than the noise. I have no idea how realistic any of the numbers I’ve assumed here actually are, and would be glad to learn of credible estimates—though of course this is a toy model at best whatever numbers one plugs in.)
Kudos for explicitly writing out your nuanced position on a high-likelihood-of-mindkill issue.
Thanks. Though that high likelihood of mindkill makes it (1) more likely that someone will try to correct my obvious stupid errors when in fact I’m right and they’re confused, and (2) more likely that someone will rightly correct my obvious stupid errors when in fact they’re right and I’m confused but I won’t believe them. Still, the best we can do is the best we can do :-).
Note that the number of people who are in jail doesn’t merely depend on how many commit crimes, it depends on how many get caught committing crimes, and that such a statistic would anticorrelate with intelligence is very nearly obvious to me.
(I agree with most of the rest of your comment.)
Yes, that’s a good point. How big the effect is depends on how the probability of getting caught varies with intelligence: I agree that it will almost always anticorrelate, but the dependence could be very strong or very weak. Anyone got any statistics on that?
I’d guess people who commit crimes but don’t get caught are very, very hard to get statistics about.
Hmm. It might be possible to indirectly get some information about them by comparing the kinds of people that get caught for premeditated crime with the kinds of people that get caught for crimes of impulse, and then adjusting for any correlation of intelligence with self-control. The latter ought to be harder to cover up.
It quite easy to make wrong arguments in favor of positions that are true. If you think that an argument is good just because you think it’s conclusion is true it’s time to pause and reflect and look at a situation where the same structure of the argument would lead to a conclusion that’s false.
Even if men and woman are on average equally qualified that doesn’t mean that a specific subset is. For a hiring manager it’s not important whether there’s causation. Correlation in the data set is enough.
I agree, that’s a very bad sign. On the other hand, there’s nothing very alarming about thinking an argument is more persuasive when you agree with its premises. And often the premises and the conclusions are related to one another. That seems to me to be exactly the situation here.
Premise: There pretty clearly isn’t an enormous cognitive difference between men and women that makes women much less competent at brainwork, so much less competent that a moderate amount of information about a person’s abilities leaves a lot of male-female difference un-screened-off.
Argument: If indeed there isn’t, then the best explanation of findings of the sort we’ve been discussing is prejudice in favour of men and against women that has substantial impact on hiring.
Conclusion: There probably is such prejudice, and it probably leads (among other things) to underrepresentation of women in many brainwork-heavy jobs.
(Note: the premise, the argument, and the conclusion are all sketchy approximations. Filling in all the details would make the above maybe 20x longer than it is.)
I find the argument somewhat persuasive. This is partly because I find the premise plausible; some people might not (e.g., because the evidence they think they have regarding the relative abilities of men and women differs from the evidence I think I have); those people will find it less persuasive.
The premise in question is not the conclusion of the argument. It is not equivalent to the conclusion of the argument. It neither implies nor is implied by the conclusion of the argument. It is, for sure, somewhat related to the conclusion—e.g., by the fact that they are premise and conclusion of a short and simple argument—and doubtless there is a correlation between believing one and believing the other. I do not find this sufficient reason to think that finding the argument more credible if one accepts the premise is any sort of cognitive error.
Perhaps I am misunderstanding your argument somehow. I confess I don’t find it perfectly clear. Would you like to make it more explicit what error you think I am committing and why you think that?
I agree and am not aware of having said or implied otherwise. One of the many modifications that would be needed to turn the argument-sketch above into something unambiguous and quantitative would be to replace “between men and women” with “between men applying for lab manager posts and women applying for lab manager posts”. If you think this makes an actual difference in here, I’d be interested to see the details.
Depends on the details, of course, but mostly yes. Once again, though, I am having trouble working out what I’ve said that suggests I think otherwise.
And/or if the argument is less clear to other people because they think it supports the outcome that they don’t like they are engaging in motivated cognition.
By the same logic you could say that someone who hires people with high SRT scores engages in SRT bias. Someone who hires based on SRT scores could simply reasonably believe that people with high SRT scores are more competent.
Google’s HR department has a variety of factors on which it judges candidates. A few years afterwards they reevaluate their hiring decisions. They run a regression analysis and see which factors predict job performance at Google. They learn from that analysis and switch their hiring decision to hiring people which score highly on the factors that the regression analysis found predictive.
That’s how making rational hiring decisions looks like. In the process they found that college marks aren’t very relevant for predicting job performance. Being good at Fermi estimates unfortunately isn’t as well, so those LW people who train Fermi estimates don’t get benefits anymore when they want to get a job at Google.
Given current laws Google is not allowed to put values such as gender into the mix they use to make hiring decisions. That means that Google can’t make the hiring decisions that maximize predicted job performance.
The politics of the issue also make it pretty bad PR for them to publish results about the effects of a model that includes gender if the correct value in the regression analysis would mean worse chances for woman getting a job. It’s good PR for them if the correct value would mean to favor woman. No big company that does regression analysis on job performance published data that favoring in gender would mean hiring more woman. Factoring in gender into a regression analysis would mean that any bias against woman in subjective competence evaluations in interviews would be canceled by that factor.
Just imagine if a big company would find that by putting gender into their regression analysis they would hiring more women and get better average job performance as a result. Don’t you think those companies would lobby Washington to allow them to put gender into hiring decisions? The silence on the issue speaks.
It could be that the silencing of feminists who want to prevent “privileged” from talking about the issue is strong enough that rational companies don’t dare to speak about their need to change their hiring practices to hire more woman via making data driven arguments. If that’s the case that says a lot about the concept of privilege and it’s problem in shutting down rational arguments.
Imagine that academic performance has a really low value for predicting job performance. People that spend a lot of time preparing for tests get better academic marks. Woman spent more time than men preparing for academic tests. That means a woman of equal competence scores higher because she puts in more work. The test isn’t anymore a strict measure of competence but a measure of effort at scoring highly of the test. In that scenario it makes sense to infer that a woman with the same test score as a man is likely less competent as the man as long as you are hiring for “competence” and not for “putting in effort to game the test”.
If you write down the math you see that it depends on your priors for the effect size of how gender correlates with job performance.
Sure. It is possible to construct possible worlds in which the behaviour of the academic faculty investigated in this study is rational and unbiased and sensible and good. The question is: How credible is it that our world is one of them?
If you think it is at all credible, then I invite you to show me the numbers. Tell me what you think the actual relationship is between gender, academic performance, job performance, etc. Tell me why you think the numbers you’ve suggested are credible, and why they lead to the sort of results found in this study. Because my prediction is that to get the sort of results found in this study you will need to assume numbers that are really implausible. I could, of course, be wrong; in which case, show me. But I don’t think anything is achieved by reiterating that it’s possible for the results of this study to be consistent with good and unbiased (more precisely: “biased” only in the sense of recognizing genuine relevant correlations) decisions by the faculty. We all (I hope) know that already. “Possible” is waaaaay too low a bar.
Making wrong arguments isn’t good even if it leads to a true conclusion. I haven’t argued that the world happens to be shaped a certain way. I argue that your arguments are wrong. LessWrong is primarily a forum for rational debate. If you arguing for a position that I believe to be true but make arguments that are flawed I will object. That’s because arguments aren’t soldiers.
On the matter of the extend of gender discrimination I don’t have a fixed opinion. My uncertainty interval is pretty large. Not having a small uncertainty interval because you fall for flawed arguments matters. The fact that humans are by default overconfident is well replicated.
But if we become back to grades as a predictor: Google did find that academic performance is no good predictor for job performance at Google.
Of course Google won’t give you the relevant data as an academic does, but Google is a company that wants to make money. It actually has a stake in hiring high performing individuals.
While we are at it, you argue as if scientific studies nearly always replicate. We don’t live in a world where that’s true. Political debates tend to make people overconfident.
It looks to me as if that’s because you are treating them as if they are intended to be deductive inferences when in fact they are inductive ones.
At no point have I intended to argue that (e.g.) it is impossible that the results found in this study are the result of accurate rational evaluation by the faculty in question. Only that it is very unlikely. The fact that one can construct possible worlds where their behaviour is close to optimal is of rather little relevance to that.
Among people actually hired by Google. Who (1) pretty much all have very good academic performance (see e.g. this if it’s not clear why that’s relevant) and (2) will typically have been better in other respects if worse academically, in order to get hired: see e.g. this for more information.
I conjecture that, ironically, if Google measure again, they’ll find that GPA became a better predictor of job success when they stopped using it as an important metric for selecting candidates.
Not intentionally. I’m aware that they don’t. None the less, scientific studies are the best we have, and it’s not like there’s a shortage of studies finding evidence of the sort of sex bias we’re discussing.
“Best we have” doesn’t justify a small confidence interval. If there no good evidence available on a topic the right thing to do is to be uncertain.
The default way to act in those situations is to form your opinions based on meta-analysis.
You basically think that a bunch of highly paid staticians make a very trivial error when a lot of money is at stake. How confident are you in that prediction?
I agree. (Did I say something to suggest otherwise?)
Given the time and inclination to do the meta-analysis (or someone else who’s already done the work), yes. Have you perchance done it or read the work of someone else who has?
Not very.
[EDITED to fix a punctuation typo]
On this topic it seems like your position is that you know that employers act irrationally and don’t hire woman who would perform well. My position is that I don’t know whether or not that’s a case. That means you have a smaller confidence interval. I consider the size of that interval unjustified.
In the absence of that work being done it’s not good to believe that one knows the answer.
My position is that I’ve seen an awful lot of evidence, both scientific and anecdotal, that seems best explained by supposing such irrationality. A few examples:
The study we’ve been discussing here.
A neurobiologist transitions from female to male and is immediately treated as much more competent.
Another study of attitudes to hiring finding that for applicants early in their career just changing the name from female to male results in dramatically more positive assessment. (The differences were smaller with a candidate several years further into his/her career.)
A famous study by Goldberg submitted identical essays under male and female names and found that it got substantially better assessments with the male name. (I should add that this one seems to have been repeated several times, sometimes getting the same result and sometimes not. Different biases at different institutions?)
Auditioning orchestral players behind a screen makes women do much better relative to men.
In each case, of course one can come up with explanations that don’t involve bias—as some commenters in this discussion have eagerly done. But it seems to me that the evidence is well past the point where denying the existence of sexist biases is one hell of a stretch.
I’m not really commenting on the object-level issue, just on the dubious logic of claiming that the name can’t matter if everything else is equal. In practice I’d guess it’s likely that the difference in rating is larger than justified.
I’m not sure anyone’s quite claiming that.
Just that if you asked, ahead of time, a question like “So, what would it take to convince you beyond reasonable doubt that there’s bias favouring men over women in the academic employment market?”, the answer you’d get would likely be pretty much exactly what this study found.
Of course, there are always loopholes, just like a sufficiently ingenious creationist can always find contrived explanations for why some scientific finding is compatible with creationism. The speed of light is changing! The aftermath of Noah’s flood just happened to deposit corpses in the layers we find in the fossil record! The world was created with the appearance of great age! Similarly, we can find contrived explanations for why an identical-looking application gets such different assessments depending on whether it’s thought to come from a man or a woman. They might be really worried about maternity leave, and choose to define taking maternity leave as a variety of incompetence! There might be differences in competence between men and women that make a big difference to scientific productivity but are completely undetectable by academic testing and unmentionable by faculty! There might be really big differences that everyone conspires not to admit to the existence of! Sure, there might. And the earth might be 6000 years old.
If this is indeed the case than why isn’t the system approaching an equilibrium similar to the one the system reached for Asians, Irish, and Scottish Highlanders?
I don’t think I can usefully attempt to answer the question, because it isn’t perfectly clear to me (1) what sort of “equilibrium” you have in mind or (2) why you think I should “if this is indeed the case” expect the system to approach such an equilibrium. The linked article, consisting mostly of several pages of Macaulay, doesn’t do much to make either of those things clear to me.
Would you care to be more explicit?
The point is that Asians, Irish, and Scottish Highlanders were able to overcome negative stereotypes and “microagressions”, and whatever other epicycles the SJW crowd feels like inventing, towards them. Why not blacks and women? You know maybe there really are innate differences involved here.
The question seems like it has a false premise, namely that women and black people haven’t made progress in overcoming those things. In fact the treatment of both groups has improved tremendously over, let’s say, the last 50 years. Which is roughly what we might expect if in fact much of the difference in how they’d been treated before was due to bias.
(It’s probably also what we’d expect if the difference was not due to bias and these groups gained in political power for some reason other than having their genuine merits recognized better. So I’m not claiming this as positive evidence for that bias. But your argument, if I’ve understood it right, is that the bias theory must be wrong because if it were right then the treatment of these groups would be improving—and in fact it is improving. I’m not aware of any reason to think it’s converged to its final state.)
I agree the “treatment” has improved. They still can’t make it in intellectually demanding occupations except by affirmative action. Let’s take the most technologically innovative part of the economy: Silicon Valley. Men massively outnumber women in technology jobs, as for race Blacks are massively underrepresented and Asians are massively overrepresented.
To avoid begging the question, that should be “don’t”.
200 years ago it was basically unthinkable for most women to have any role other than parent and housekeeper. 50 years ago it was basically unthinkable for women to have senior leadership roles or to work in the most intellectually demanding jobs. Now it is thinkable but uncommon; at least some of them appear to do pretty well but they are few in number. Prima facie, the continuing underrepresentation could be because of differences in ability distribution or personality traits or sometihng; or because of (reduced but still remaining) prejudice; or some mixture of both.
Your argument a couple of posts back, if I understand it right, was: It must be because of differences in ability, because otherwise they’d be doing OK now just like East Asians are. So far as I can see, that argument only works if there’s some reason to think that if the past shortage of women in those roles were the result of prejudice, then by now it would be completely repaired. But I see no reason to expect that; prejudices can last a very long time. It looks to me (though I don’t have statistics; do you?) as if the current rate of change in women’s career prospects is still substantial, suggesting that if the last few decades’ changes are the result of prejudice reduction then the process isn’t yet complete and we shouldn’t assume that we are now at the endpoint of the process.
Note also that there were no people tacking about “microagressions” or for that matter much in the way of affirmative action when these groups succeeded.
Also, the closing of the gender gap appears to have stopped during the last 30 years.
That language seems to presuppose that whatever change they achieved has now stopped. As I said above, I think that’s very far from clear.
That post seems long on anecdote and short on data.
Pages 10-11 of this document seems to show a steady decline in full-time gender pay gap from 1970 to 2010. The part-time figures are weirdly different; by eye they seem to show one downward jump circa 1974, then approximate stasis, then another downward jump circa 2005.
What it would take to show that there is bias favoring men over women would involve showing that men are more likely to be hred than women and that this imbalance in hiring rate is not justified.
If you apply a high cutoff the difference is pretty big.
In the present case—as you would see if you looked at the study in question, which I therefore guess you haven’t—the level of ability we’re looking at (for “male” and “female” candidates) is not super-high, and in particular isn’t high enough for the sort of variance difference you have in mind to make a big difference.
These are candidates with a bachelor’s degree only, GPA of 3.2, and all the information in the application designed to make them look like decent but not stellar candidates for the job. We’re not talking about the extreme tails of the ability distribution here; the tails have already been cut off.
All the listed information is actually remarkable little. Like I said below the most “objective” thing on your list is the GRE score and even standardized test scores have high variance.
Would that “everything” include things like college degrees, remember affirmative action is a thing in college admissions. Also, an applicant’s sex conveys information, are you sure the other information was enough to completely screen that out? The other thing to take into account is that if I hire a women and she doesn’t work out, I risk getting hit with a wrongful termination suite if I fire her.
They took the exact same application, sometimes with male-looking names and sometimes with female-looking names, and asked faculty for their opinions about them. The female versions were rated substantially (and significantly at the 0.001 level) worse for “competence”, “hireability” and “willingness to mentor this student”. The gap in estimated competence was about the same in size and significance as the gaps in the other metrics, which to me seems to indicate that differences in fear of a wrongful termination suit didn’t contribute much if at all. (On looking at the relevant bit of the paper, the authors agree and have some statistical analysis that allegedly supports this view.)
When asked roughly what starting salary they’d offer the applicants, the “female” applications attracted ~12% lower figures.
(The details are all there at the other end of the link I gave.)
I’m not completely sure of anything, ever. But: The information included: age, degree granted and university that granted it, GPA, GRE scores, extracts from application letter and faculty letters of recommendation, etc. If there’s any residual information to speak of in knowing whether the applicant was male or female, I’d be rather surprised; if there’s enough to justify the differences found in the study, I’d be flabbergasted.
[EDITED to add: While affirmative action may be “a thing in college admissions”, to the best of my knowledge it is not “a thing” in the awarding of college degrees, the calculation of GPAs, etc.]
If women are more likely to use maternity leave or otherwise devote more resources to family and less to the job than men are, and if they are more likely to sue for sexual harassment than men, then most of these assessments could be correct; seeing a female name actually does give information.
As I have said a few times already in this thread, the numbers make it look very much as if the dominating factor was an assessment that the “female” candidates were less competent than the “male” ones. Lack of commitment and increased lawsuit risk don’t seem to me like matters of competence and I would expect the faculty surveyed to share that opinion.
Do you have a rough estimate of (1) how much more likely women would have to be than men to do those things, in order to justify a difference in evaluation of the magnitude found by this study, and (2) how much more likely women actually are to do those things?
(Two remarks in regard to sexual harassment lawsuits. 1: I think the relevant figure isn’t how much more likely women are to file such suits but how much more likely they are to file them when no harassment has really occurred. But perhaps not: suppose women are more likely to be victims of sexual harassment sufficient to justify a lawsuit, and therefore more likely to file such lawsuits; then one possible position would be to consider women less desirable employees on those grounds and rate them as less competent. Personally, I think that would be odious, but I can imagine that some people might disagree. 2: My understanding is that actually such lawsuits are really rather rare, much too rare for rational consideration of their risk to yield the reported difference in evaluation even if (a) all such lawsuits are assumed groundless but successful and (b) the resulting losses in productivity and collegiality are assigned to lack of “competence” by the person filing the lawsuit. However, I don’t have extensive statistics on this and will be happy to be corrected if wrong.)
The problem is that “whether sexual harassment has occurred” isn’t all that well-defined. You can of course define “sexual harassment” however you want but then you have to establish you it’s a bad thing. For example, from a briefing at the company I work at the examples of “sexual harassment” was:
1) a woman goes to work in somewhat provocative/revealing clothing and a male coworker complements her on her appearance.
2) a manager used the phrase “guys and gals”.
Frankly if these examples are typical of “sexual harassment”, I’d say sexual harassment isn’t a problem.
Did either of these examples result in lawsuits?
I don’t know, the presenter didn’t say. Although the fact that these were presented as examples of behaviors not to engage in, is telling. Also even if they don’t bring a lawsuit, the fact that they make an issue out of these kinds of things is not conducive to a good work environment.
Of course I wasn’t there. But it occurs to me that there are several reasons why “marginal” examples might actually be the most useful:
To define the region of (concept-)space a thing occupies, you might want to point to a few places on its boundary.
There’s little point telling people “raping your co-workers is bad; don’t do it” because anyone to whom that isn’t already obvious is probably a lost cause.
Marginal examples might be more likely to provoke useful discussion.
I’d put the examples you give in the category of (not typical examples of sexual harassment, but) things that are frequently harmless but (1) might cause easily-avoided annoyance or upset in some cases and so should maybe be avoided and (2) in some cases might indicate, or be thought to indicate, an underlying bad attitude (women in the workplace being seen primarily as eye candy; women being seen as lower-status and akin to children).
I repeat: of course I wasn’t there and don’t know exactly what your presenter said about these examples. If s/he said “these things are definitely harassment and you could get in serious trouble for doing them” then I’d regard that as unreasonable; if s/he said “these things may seem harmless, and often they are, but you should still avoid them”, I’d agree.
Anyway, I mention all this just in the interests of mutual understanding; it’s all kinda irrelevant to the question of whether “greater risk of sexual harassment lawsuits” is a good justification for rating an identically-described person as substantially more “competent” if they have a male name than a female name. Do you really think it is?
The problem is that it causes people to treat it as an archetypical example.
I fail to see why it should be policy to cater to people who are clearly being unreasonable.
For one thing, because being unreasonable is simply What People Do and it seems better to care about outcomes in the real world than outcomes in some imaginary world where everyone is always reasonable. So if doing something predictably results in a bunch of people being upset, then it might be better to avoid it even if it would be better for everyone if they weren’t upset by it.
For another, because what’s “clearly unreasonable” to one person may be “clearly reasonable” to another. It may seem “clearly unreasonable” for a woman to have a problem with having her appearance complimented by her male colleagues. But if what she’s found is that over and over again her male colleagues comment on her (and other women’s) appearance, and never on their ideas, while the reverse happens to the men around her … why, then, I have some sympathy if she gets frustrated by yet another compliment on her appearance. (It might in some sense be better for her to focus not on the compliments on her appearance but on the absence of response to her work. But actual things that actually happen are easier to see and more psychologically salient than absences, even when the absence is the bigger underlying problem.)
Only people who are—how shall I put it? -- clearly being unreasonable. One might prefer not to make policy on the basis of people who are clearly being unreasonable :-).
Seriously: yes, I agree that that’s a potential problem. The obvious solution seems to me to be to make it as clear as you possibly can when you’re talking about central examples and when you’re sketching the boundaries. Unfortunately, I bet there will always be (clearly unreasonable) people who don’t take any notice and either mix the two up or pretend to. I’m not sure much can be done about that.
I mostly agree (and upvoted), but...
Well, complimenting people wearing attractive clothes is is simply What People Do and it seems better to care about outcomes in the real world than outcomes in some imaginary world where no-one ever notices other people’s clothes. So if wearing certain clothes predictably results in a bunch of people commenting on your appearance (and it annoys you), then it might be better to wear more modest clothes yadda yadda yadda.
;-)
You say that like you expect me to disagree, but I don’t think I do. (But I would generally avoid saying so to the people in question, which I might not on the other side, because it seems more obviously unreasonable to have to avoid wearing nice clothes to work than to have to avoid complimenting people’s clothing at work. I’m not terribly sure how much sense that makes, though.)
It seems even more unreasonable to be to wear sexy clothes (how did “sexy” turn into “nice”?) and then object when someone comments on them. Frankly the only way I can explain the woman’s actions are that she was either insulted that the complementer was too low status or trolling for an excuse to accuse someone of sexual harassment.
I don’t think it did, exactly. I just didn’t assume that clothes that could be described as “somewhat provocative/revealing” necessarily belonged in the bucket labelled “sexy” rather than the one labelled “nice”.
To be more precise: (1) what is viewed as provocative or revealing is highly dependent on who’s doing the viewing (see, e.g., Victorian England or many Muslim-dominated places today; but similar variation occurs at the individual as well as the societal level), and (2) person A may wear clothes that person B finds “revealing” without the least intention of attracting sexual attention of any sort.
I have no quantitative data (and doubt whether any exist) but have more than once heard women complain that their choice of clothing was treated by a man as some sort of attempt to provoke when in fact they were just wearing something they felt comfortable in or liked the look of. (I have a feeling there is pretty decent scientific evidence that men tend to overestimate the extent to which women’s behaviour is intended to signal sexual availability or interest, but don’t have references to hand. It seems like a plausible hypothesis on the usual handwavy evo-psych grounds, for what little that’s worth.)
I don’t know what she was wearing, I heard it from the lawyer doing the briefing, but he did mention her undoing some buttons. In any case, if I came to work wearing a suite, we dress casually, I’d expect people to comment on it.
I was about to go ‘sweatshirts for example are comfortable but definitely not provocative’, then I remembered reading that when men talk about comfortable clothes they tend to mean physically comfortable whereas women tend to mean socially/psychologically comfortable (as in this comment, though I don’t know if Nornagest is a woman).
(Then again, being comfortable in the latter sense with wearing certain clothes but not with being complimented for them sounds weird to me.)
Sure. It sounds a bit weird to me too, for what it’s worth. But the whole point here is that the reasons why something is unpleasant to one person may be far from apparent to another. Anecdotally, it seems that many women have the experience of being persistently treated (so to speak) as ornamental rather than functional, of having their male colleagues pay attention to their appearance while neglecting their work. Someone in that situation may not be glad of compliments to her appearance even if she has gone to some trouble to look good.
An analogy occurs to me. Let’s suppose that an important part of your employment is writing analytical reports of some kind. Stock market forecasts, competitive analysis of other companies’ products, software requirements, that sort of thing. You write these reports. You hand them over to your boss. And he takes a look and says “Nice choice of font.” or “I see you spelled ‘accommodate’ correctly, well done.” A single instance of this is harmless and you’d probably be glad of it. But it happens again and again, much more often than any substantive comment (positive or negative) on the actual content of the reports you’re writing. After a while, you might start taking these comments as indicating that your boss either thinks the content is no good, or for some reason simply doesn’t much care about the content. You might find that being complimented on your excellent use of quotation marks makes you feel bad, not good, about how valuable your carefully calculated and checked risk assessment is to the company.
And you might feel that way even if, as a matter of fact, you did put some care and skill into spelling and punctuating correctly and presenting the report attractively.
Now who’s making highly implausible theories and arguing that they’re “possible”?
Well, if I had made an unusual choice of font, I’d expect that reaction.
It doesn’t appear to me to be a highly implausible theory; it’s a thing many women actually complain about.
My understanding is that quite a few women report male attention going disproportionately to their clothes and appearance even when they aren’t wearing anything very unusual.
Also, there are other employees around who are proud of their use of quotation marks and specifically expect that they be complimented on them. Some of them even leave reports on their desks with pages of words prominently displayed just so that people will compliment them on their punctuation.
And there are even more employees who really want to be complimented on their use of quotation marks, but only from people with small noses. This unusual preference is something they don’t want to admit, so these other employees, when complimented by someone with a big nose, pretend to be like you and be offended because they are not being complimented on content, when that’s not true at all.
I think in an environment like that you should expect to get complimented on your punctuation quite a bit.
The problem with compliments isn’t so much that woman often don’t enjoy getting them. There are many cases where they don’t, but that’s not the central issue.
The problem is that it’s hard for a man to compliment a woman on her appearance and at the same time not let it influence how he treats the woman in their professional function. The availability heuristic is a central part of how humans make decisions and if the attribute that most available is “attractive” instead of “skilled-at-job” that matters.
On the other hand the halo effect also exists.
The problem with the problem is that not everyone actually means that. And the ones who don’t mean it end up reducing the credibility of the people who say it and really mean it.
Sure. But after a couple times I compliment on your punctuation and you don’t take it well, I should get the hint and realize that you aren’t one of those people. (And whether you do like to be complimented on punctuation by people with smaller noses¹ than mine is irrelevant; if you don’t like it when I do it, I should stop it, at least until I can afford a rhinoplasty.)
I was about to go ‘but there’s a large difference between writing in a formal standard grammatically correct way and writing in a way that fishes for compliments!’, then I remembered that that’s probably much less the case in the America than where I am (see e.g. [1], [2]; by comparison where I am you can just wear canvas sneakers or tennis shoes, jeans, and a T-shirt or a sweater, and that’s not necessarily considered sexy but not necessarily slovenly either, regardless of your gender), so never mind.
“Native speakers” would be a less silly allegory, BTW.
Using your analogy of native speakers, people want to be complimented on their punctuation by native speakers only. When complimented by anyone who doesn’t speak well enough, they lie and say “I don’t like it because you’re not complimenting me on the quality of my work”, when they’re really just using it as a cover for an implied insult of “I hate people with your accent”. This proceeds to the point where everyone knows that the former complaint is just an excuse for the latter.
Then you come along, and you really want to be complimented on the quality of your work. You’re going to be mistaken for those other guys quite a bit.
Doesn’t change my point. If you are predictably annoyed when I compliment on your punctuation and I know it, I’d better stop it if I don’t want to be a dick, regardless of why it annoys you.
I don’t believe that. For instance, if you are white, I am not, and you are offended by compliments because you are offended whenever a non-white person talks to you or even sit next to you, it’s not me that’s being a dick by offending you, it’s you who’s being one by being offended by things that you have no right to be offended by.
That’s essentially what’s going on here—some people who are offended are offended for a reason that doesn’t deserve to be respected (they dont like someone’s accent/they don’t want to be complimented by someone low status), and they lie and pretend they are offended for a reason that does deserve to be respected (they don’t want shallow compliments).
Not wanting to be complimented for being sexy by unsexy people doesn’t deserve to be respected? WTF? Would you be okay with it if someone you’re not only not attracted to in the slightest but perhaps even repulsed by said something to the effect that they would like to bang you (even though not with those words)?
I might want to restrict such things to being said only by someone who I’m in a relationship with, but that’s different from restricting such things to only being said by all beautiful people.
Then it’s not a lie. That’s not how natural languages work. If everybody knows that when people say X they mean Y, then X means Y, regardless of etymology. There’s no stone tablet in the sky that specifies what X actually means regardless of when people actually say X and when they don’t. (Or would you say that someone saying “it’s raining cats and dogs” in absence of domestic carnivorans falling down from clouds is lying?)
And if of the possible ways of wording a complaint someone chooses the one least likely to hurt my feelings, why should I hold it against them, rather than being grateful for that?
Hold on. I’m not arguing that X doesn’t mean Y. I’m arguing that X does mean Y, and that explains why people treat Y as X. (X=I don’t want to be complimented by ugly/low status people, Y=I don’t want to be complimented based on superficial attributes, by anyone).
Tapping out.
I meant “comfortable” as an attribute of the social situation in that comment, not of the clothes I’d be wearing in it. If I were wearing sweatpants to a wedding, for example, I’d likely find them comfortable but I wouldn’t be comfortable.
(I’m a guy.)
Well, that’s not obvious to me, anyway...
Well, these aren’t mutually exclusive. Can’t we do both? Postel’s law, anyone?
Postel’s law would mean not throwing a fit when someone complements your clothing.
Yes, that too.
I thought that was what I was suggesting is best—at least if it happens that the women in question can actually avoid having the men focus on their appearance by making changes in clothing. I can’t help suspecting (though I have no actual evidence) that in such cases their options are actually “get unwanted compliments from men who focus on their appearance and ignore their ideas” and “get unwanted critical comments from men who focus on their appearance and ignore their ideas”, with perhaps a little middle ground where they get both positive and negative comments on their appearance and still have their work overlooked.
While lawsuits may be rare, they are expensive, and people are risk-averse.
Also, the range of behavior that has to be avoided to avoid an unjustified lawsuit is much wider than the range of behavior that has to be avoided to avoid a justified lawsuit, and since even unjustified lawsuits are expensive, the former category is what really matters.
Your second paragraph seems to be agreeing with the first of my parenthetical points, but it sounds as if it’s intended to be a point of disagreement. I mention this just in case it turns out that one of us has misunderstood the other.
Unjustified lawsuits are probably cheaper—you’re more likely to win them, more likely to win them quickly, and more likely (in jurisdictions where this is a real distinction) to have the plaintiff have to pay your legal costs.
It was disagreeing with your second point, “much too rare for rational consideration of their risk to yield the reported difference in evaluation”. If the person is risk-averse, then it’s not too rare for rational consideration of the risk to yield the difference. (Don’t assume that risk aversion is inherently iirational. It’s not.)
I don’t understand. It was your first paragraph that was pointing out risk aversion. The second paragraph was the one about unjustified versus justified lawsuits. (Let me try to bridge one possible inferential gap by remarking that I think unjustified sexual harassment lawsuits are also very rare.)
For a lot of colleges the hard part is getting in, and getting the degree isn’t that hard conditional on getting in.
That would be why the application also included the applicant’s GPA. And also both GRE scores. And a bunch of other things.
GPA is meaningless without knowing how hard the classes the applicant took were.
So is your claim that the scores on a single GRE test completely capture everything about an applicant relevant to job performance?
I find your question absolutely bewildering, given that the very sentence I wrote that mentioned GRE scores mentioned them only as part of a list of things.
Yes and when I pointed out the problems with all the other things in the list your reply basically amounted to “you haven’t made any objections to GRE scores”.
You didn’t point out the problems with all the other things in the list, you made a claim about one thing in the list. My reply did not (as I have already pointed out) amount to “you haven’t made any objections to GRE scores”.
Regardless, no metric is perfect, and no one has been claiming otherwise. Accordingly, it is possible in principle (as I have already said more than once in this discussion) that there might be male/female differences that are either really huge, or highly relevant to scientific competence but startlingly uncorrelated with all the information provided to the faculty in this study, and that render the assessments they made rational given the information they had.
However, it seems pretty unlikely to me.
What do you think? Is the best explanation for these very different assessment of identical applications from differently-named candidates, in your opinion, that the faculty making the assessment are aware of such huge differences between men and women and have weighed them roughly correctly (not necessarily consciously and explicitly) to arrive at the results that have? If so, could you sketch for me roughly what these differences are and how they lead to that result? Because I’m having real trouble thinking of any hypothesis of this sort that’s consistent with what I think I’ve observed of the relative abilities of men and women.
Do I believe that Americans are generally more intelligent than Europeans? No, I don’t. At the same time in the LW census the average American has somthing like a 10 point higher IQ. In the data set there a strong correlation.
I think the intuition that the factor of the name should be zero is wrong even if there no causal effect because gender simply interacts in complex ways with many other things. I’m not sure in what direction the factor is going to correct, which might also be different in different situations but assuming that it contains no information at all doesn’t seem to be right.
I just grabbed the latest LW survey data I could find, selected (1) rows with “United States” as country and something other than a null for IQ and (2) all rows with something other than a null for IQ. (Note that this doesn’t include any sort of selection on the basis of reliability of IQ score.) I got means of 138.3 for the larger dataset (472 numbers, stddev=13.6) and 140.7 for the smaller (249 numbers, stddev=13.5). I wouldn’t call that “something like a 10 point higher IQ”.
What intuition that it should be zero? The question is whether it should be very large, not whether it should be exactly zero.
I’ve already explained why the difference would need to be very large for these results to be correctly explained by saying that the rating faculty made accurate allowance for real male/female competence differences. If you missed that, or you think I got it wrong, or it didn’t make sense, do let me know.
Let’s see: there are numerous ones the most relevant are: women have less variation in intelligence then men and so there fewer unusually smart women. Women are worse at taking criticism. There is also a lot of stuff about the kind of hierarchies men and women tend to form.
Have you actually been observing the relative abilities between men and women, or is your reaction whenever you notice a woman doing something badly or acting emotionally to hit yourself for having a “sexist” thought?
That could indeed (if the numbers work out) explain a difference in success at the very highest levels in the absence of prejudice. But this sort of effect is far weaker away from the very tails of the distribution, and the particular study we’re taking as an example in this discussion is not concerned with the very tails of the distribution. Further, my understanding is that GRE scores correlate somewhat better with intelligence than they do with job performance (see, e.g., this post which has a few references to the primary literature), and I would expect them to do a pretty good job of screening off differences in raw intelligence in this case.
Evidence? (I have to say it looks to me as if people are bad at taking criticism, and I haven’t noticed a big difference between men and women; but I’ve not studied this and will be glad to learn.)
I’m afraid that’s not specific enough for me to form any idea of how it would justify a drastically lower assessment of the likely competence of a woman than an identically-credentialed man as a scientific lab manager.
Relative abilities as such are pretty much unobservable. I’ve been observing the relative performance. But only casually and qualitatively; if you have a pile of useful data then by all means point me at it.
No, not at all. I notice both men and women doing things badly and acting emotionally all the time, and feel no particular impulse to self-punishment when I do so. -- Is it your usual practice to assume that people who disagree with you are off their heads, or have I said something to give you that impression particularly strongly in my case?
(Note for the avoidance of doubt: I am assuming that you didn’t mean “hit yourself” literally; of course if you did then it’s an even weirder thing to think I might do.)