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My immediate thought when I saw this a few days ago was "sampling bias" -- not that the author had a biased sample of professional women, but rather that profes

My immediate thought when I saw this a few days ago was "sampling bias" -- not that the author had a biased sample of professional women, but rather that professional women are a biased sample of women. Given the social environment -- pushing both females and males away from what they might have preferred as a life trajectory -- I think it's very likely that the average professional woman is significantly more aggressive than the average professional man, simply because the non-aggressive women tend to not enter professional careers. This mirrors an observation I've heard from several faculty members in computer science and engineering programs: As complete populations, girls aren't any smarter than boys on average, but in those programs the girls are always among the top students -- because it's only the most exceptional girls who overcome the social factors which keep most of their peers out of those subjects. There may be a real effect here, but the evidence presented is inconclusive.

blutoot 12y ago
I don't see the problem in sampling only professional women when the hypothesis is whether professional women are rated differently than professional men. It would be problematic if this hypothesis was tested with a sample from the overall female population. Non-professional women don't have reviews to be useful to the study. What you described is an explanation for WHY they are rated different. It doesn't discredit the study methodology.
- spindritf 12y ago
  hypothesis is whether professional women are rated differently than professional men The point is that you can't know whether they're rated differently (by different criteria) or actually different.
  - lclarkmichalek 12y ago
    I think one of the premises you have to accept in this article is that the actual difference between women and men is less than (looking at the "has negative feedback" vs "only constructive criticism" chart) 72%. I don't find that a hard premise to accept
    - NotAtWork 12y ago
      I don't actually want to be arguing against this study, but without knowing how those two fields are quantified, those numbers are completely meaningless and referring to fuzzy numbers like that is one of the hallmark ways to lie with statistics. There are also lots of uncontrolled variables, such as the average woman submitting 1.4 reviews, while the average guy submitted only 1.3 reviews. This means the totals would obviously be off, even if everything were symmetric per capita, a fact not mentioned when the numbers are displayed. Further, it's likely that the discrepancy in the number of reviews per capita submitted is a sign of some underlying sampling bias, which needs to be accounted for before we can really talk about the distribution of feedback. I think this is a serious issue that needs addressing, but that's exactly why I feel it's important to object to bad math.
- NotAtWork 12y ago
  This article lacked the power to tell if the effect (ie, different language in reviews) was correlated to their gender or because of a selection bias in the people studied, eg because of a possible difference in the distribution of personality types in the field from each gender. It's possible that there's a hiring bias, and reviews are being done fairly, but show biased results when naively studied because of the underlying bias. This is what makes social statistics hard, and there are many faults in studies involving gender that fail to account for possible confounding effects in the data.
- cperciva 12y ago
  What you described is an explanation for WHY they are rated different. It doesn't discredit the study methodology. Right, and I'm not objecting to the conclusion "women in tech are described as being more aggressive than men in tech". What I'm objecting to is the logical jump from there to assuming that the difference is due to a bias in the "described" part rather than a bias in which people enter the tech field.
melindajb 12y ago
Your argument is not logical. These were professionals in the same sphere: tech. And one could make the argument that the sample of men was also biased--towards men who liked tech. No one claimed this was an iron clad peer reviewed scientific study--and I'd love to see some done on this in addition to those that already exist. Deborah Tannen is one of the more well known researchers in this area to uncover distinct gender patterns in speech that affect performance, for example. There are now hundreds and hundreds of data points, and anecdotes. At what point is there enough evidence to convince some people that there IS a problem, and believe those of us who have experienced this exact phenomenon? TBH this response is exactly what I thought I'd see on hacker news: attack the methodology, thus missing the forest for the trees.
- vezzy-fnord 12y ago
  At what point is there enough evidence to convince some people that there IS a problem, and believe those of us who have experienced this exact phenomenon? The existence of a problem is virtually undisputed, it's the nature of it that is debated. In addition, the existence of a problem does not justify misrepresenting it, even if the intention is to raise awareness.
  - melindajb 12y ago
    Exactly what part here is misrepresented?
  - conistonwater 12y ago
    > The existence of a problem is virtually undisputed This thread includes people's opinions that this is not a real effect, and is instead the result of poor methodology, sampling bias, and whatnot. It is really not fair to say that the problem's existence is undisputed. There are plenty of people who dispute it, and that's also a problem.
    - NotAtWork 12y ago
      Most of the comments (all of them that I've seen) say that the effect is real, but the source isn't necessarily a bias in the reviews, because of how the study was conducted (eg, there could be a hiring bias). Bringing up a different cause to explain an effect is not dismissing the effect as existing in the data, merely calling in to question the source of it.
anigbrowl 12y ago
As complete populations, girls aren't any smarter than boys on average, but in those programs the girls are always among the top students -- because it's only the most exceptional girls who overcome the social factors which keep most of their peers out of those subjects. Social factors like the assumption that women who consistently outrank their peers are 'significantly more aggressive'? I'm sure you mean well but your post here seems like a classic example of circular reasoning. You assume that because the total population of women entering such programs is not any smarter on average, those who consistently perform well rather than quitting must therefore be of only average intelligence, and are making up for it by being more aggressive and competitive (than, I assume, the average man). It's equally possible that women of average or median intelligence deicde they're unlikely to succeed in that field and drop out, leaving only the best female students. My wife is an EE and there were only 2 women in her graduating class out of a total of 30 or 35. She's had to put up her share of colleagues complaining about her being 'abrasive' and so on. It seems to me that this only exists relative to the complainant's prior expectations of women, eg her emails tend to be short and to the point rather than chatty or friendly. The horror.
- cperciva 12y ago
  the total population of women entering such programs is not any smarter on average Sorry, I was unclear. I meant that the total worldwide population of women is no smarter on average than the worldwide population of men. The evidence points to the subset of women who enter CS and engineering being smarter on average than the subset of men who enter CS and engineering. It's equally possible that women of average or median intelligence deicde they're unlikely to succeed in that field and drop out, leaving only the best female students. From everything I've seen it's less a matter of dropping out and more a matter of not entering those programs in the first place; but yes, there are societal influences which result in "marginal" men entering those fields while "marginal" women do not.
  - anigbrowl 12y ago
    The evidence points to the subset of women who enter CS and engineering being smarter on average than the subset of men who enter CS and engineering. Isn't this rather at odds with your hypothesis that they do well because of being more aggressive? I mean, perhaps that is true but if the data suggests that women entering those programs are in fact smarter why would your hypothesis be any more likely than the existence of bias in HR departments?
pnathan 12y ago
Let's boil that away even more: suppose that the population entering CS is representative of the total population. Then, let's suppose that the social barriers to graduation & the professional workforce are adequately high that it filters out women who are not exceptionally determined to succeed in this environment[1]. When I've talked with women about this, they generally seem to agree with that. [1] Some women get death threats over their analysis of sexism in video games. I can't think of a more hostile environment.
learnstats 12y ago
Given that the frequency with which the key critical words are applied to men (essentially never) and women (essentially always), your explanation cannot tell the whole story. Saying that this is inconclusive is a strange thing to claim - the evidence is plentiful. You are describing a serious but separate problem which adds to but does not explain this difference.
deleted 12y ago
[deleted]

blutoot 12y ago

I don't see the problem in sampling only professional women when the hypothesis is whether professional women are rated differently than professional men. It would be problematic if this hypothesis was tested with a sample from the overall female population. Non-professional women don't have reviews to be useful to the study. What you described is an explanation for WHY they are rated different. It doesn't discredit the study methodology.

spindritf 12y ago
hypothesis is whether professional women are rated differently than professional men The point is that you can't know whether they're rated differently (by different criteria) or actually different.
- lclarkmichalek 12y ago
  I think one of the premises you have to accept in this article is that the actual difference between women and men is less than (looking at the "has negative feedback" vs "only constructive criticism" chart) 72%. I don't find that a hard premise to accept
  - NotAtWork 12y ago
    I don't actually want to be arguing against this study, but without knowing how those two fields are quantified, those numbers are completely meaningless and referring to fuzzy numbers like that is one of the hallmark ways to lie with statistics. There are also lots of uncontrolled variables, such as the average woman submitting 1.4 reviews, while the average guy submitted only 1.3 reviews. This means the totals would obviously be off, even if everything were symmetric per capita, a fact not mentioned when the numbers are displayed. Further, it's likely that the discrepancy in the number of reviews per capita submitted is a sign of some underlying sampling bias, which needs to be accounted for before we can really talk about the distribution of feedback. I think this is a serious issue that needs addressing, but that's exactly why I feel it's important to object to bad math.
NotAtWork 12y ago
This article lacked the power to tell if the effect (ie, different language in reviews) was correlated to their gender or because of a selection bias in the people studied, eg because of a possible difference in the distribution of personality types in the field from each gender. It's possible that there's a hiring bias, and reviews are being done fairly, but show biased results when naively studied because of the underlying bias. This is what makes social statistics hard, and there are many faults in studies involving gender that fail to account for possible confounding effects in the data.
cperciva 12y ago
What you described is an explanation for WHY they are rated different. It doesn't discredit the study methodology. Right, and I'm not objecting to the conclusion "women in tech are described as being more aggressive than men in tech". What I'm objecting to is the logical jump from there to assuming that the difference is due to a bias in the "described" part rather than a bias in which people enter the tech field.

melindajb 12y ago

Your argument is not logical. These were professionals in the same sphere: tech. And one could make the argument that the sample of men was also biased--towards men who liked tech. No one claimed this was an iron clad peer reviewed scientific study--and I'd love to see some done on this in addition to those that already exist. Deborah Tannen is one of the more well known researchers in this area to uncover distinct gender patterns in speech that affect performance, for example. There are now hundreds and hundreds of data points, and anecdotes. At what point is there enough evidence to convince some people that there IS a problem, and believe those of us who have experienced this exact phenomenon? TBH this response is exactly what I thought I'd see on hacker news: attack the methodology, thus missing the forest for the trees.

vezzy-fnord 12y ago
At what point is there enough evidence to convince some people that there IS a problem, and believe those of us who have experienced this exact phenomenon? The existence of a problem is virtually undisputed, it's the nature of it that is debated. In addition, the existence of a problem does not justify misrepresenting it, even if the intention is to raise awareness.
- melindajb 12y ago
  Exactly what part here is misrepresented?
- conistonwater 12y ago
  > The existence of a problem is virtually undisputed This thread includes people's opinions that this is not a real effect, and is instead the result of poor methodology, sampling bias, and whatnot. It is really not fair to say that the problem's existence is undisputed. There are plenty of people who dispute it, and that's also a problem.
  - NotAtWork 12y ago
    Most of the comments (all of them that I've seen) say that the effect is real, but the source isn't necessarily a bias in the reviews, because of how the study was conducted (eg, there could be a hiring bias). Bringing up a different cause to explain an effect is not dismissing the effect as existing in the data, merely calling in to question the source of it.

anigbrowl 12y ago

As complete populations, girls aren't any smarter than boys on average, but in those programs the girls are always among the top students -- because it's only the most exceptional girls who overcome the social factors which keep most of their peers out of those subjects. Social factors like the assumption that women who consistently outrank their peers are 'significantly more aggressive'? I'm sure you mean well but your post here seems like a classic example of circular reasoning. You assume that because the total population of women entering such programs is not any smarter on average, those who consistently perform well rather than quitting must therefore be of only average intelligence, and are making up for it by being more aggressive and competitive (than, I assume, the average man). It's equally possible that women of average or median intelligence deicde they're unlikely to succeed in that field and drop out, leaving only the best female students. My wife is an EE and there were only 2 women in her graduating class out of a total of 30 or 35. She's had to put up her share of colleagues complaining about her being 'abrasive' and so on. It seems to me that this only exists relative to the complainant's prior expectations of women, eg her emails tend to be short and to the point rather than chatty or friendly. The horror.

cperciva 12y ago
the total population of women entering such programs is not any smarter on average Sorry, I was unclear. I meant that the total worldwide population of women is no smarter on average than the worldwide population of men. The evidence points to the subset of women who enter CS and engineering being smarter on average than the subset of men who enter CS and engineering. It's equally possible that women of average or median intelligence deicde they're unlikely to succeed in that field and drop out, leaving only the best female students. From everything I've seen it's less a matter of dropping out and more a matter of not entering those programs in the first place; but yes, there are societal influences which result in "marginal" men entering those fields while "marginal" women do not.
- anigbrowl 12y ago
  The evidence points to the subset of women who enter CS and engineering being smarter on average than the subset of men who enter CS and engineering. Isn't this rather at odds with your hypothesis that they do well because of being more aggressive? I mean, perhaps that is true but if the data suggests that women entering those programs are in fact smarter why would your hypothesis be any more likely than the existence of bias in HR departments?

pnathan 12y ago

Let's boil that away even more: suppose that the population entering CS is representative of the total population. Then, let's suppose that the social barriers to graduation & the professional workforce are adequately high that it filters out women who are not exceptionally determined to succeed in this environment[1]. When I've talked with women about this, they generally seem to agree with that. [1] Some women get death threats over their analysis of sexism in video games. I can't think of a more hostile environment.

learnstats 12y ago

Given that the frequency with which the key critical words are applied to men (essentially never) and women (essentially always), your explanation cannot tell the whole story. Saying that this is inconclusive is a strange thing to claim - the evidence is plentiful. You are describing a serious but separate problem which adds to but does not explain this difference.

deleted 12y ago

[deleted]