High-achieving men and women are described differently in reviews(fortune.com)
fortune.com
High-achieving men and women are described differently in reviews
http://fortune.com/2014/08/26/performance-review-gender-bias/
89 comments
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.
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.
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.
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.
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?
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?
> sn't this rather at odds with your hypothesis that they do well because of being more aggressive?
I don't think that's what he said originally. He said that aggressive women are those who overcome the social pressure to not join a male dominated field like CS/tech.
To give an extreme example, you can be a timid man and still join CS simply because there's no pressure against you doing so, but if you were a timid woman you wouldn't be able to overcome the poor atmosphere women in STS face.
I don't think that's what he said originally. He said that aggressive women are those who overcome the social pressure to not join a male dominated field like CS/tech.
To give an extreme example, you can be a timid man and still join CS simply because there's no pressure against you doing so, but if you were a timid woman you wouldn't be able to overcome the poor atmosphere women in STS face.
Yes, that's what I was trying to say.
Well, as a woman doing a computer science PhD, I'll say I initially felt that my advisor didn't respect my opinions, always argued against my ideas, even though I was better informed much of the time (and that's normal, he only has a mile-high view of my thesis work). This made me angry, and I didn't hesitate to show it. I stood up for myself and I must have come off as abrasive at times. Other factors may have contributed (I'm now the most senior student in the lab), but I feel like he treats me with more respect now, and our relationship has much improved.
Not to discount your experiences (obviously I have no idea about the details), but I know some faculty who are dismissive of all their students' ideas -- and deliberately so, based on the argument that until a student is able to stand up for their ideas, they're not ready to receive a PhD.
Personally I think it's an unnecessarily cruel approach, but it does seem to produce good results at times.
Personally I think it's an unnecessarily cruel approach, but it does seem to produce good results at times.
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.
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.
At what point is there enough evidence to convince some people that there IS a problem
I'm not disputing the fact that there is a problem. I'm sure there are lots of problems, in fact.
What I'm saying is that it's facile to observe that women in tech are more often described as being aggressive and to assume that this is a problem with how people are described; it would be equally consistent with the evidence to conclude that the problem is one of non-aggressive women never getting hired into this field.
I'm not disputing the fact that there is a problem. I'm sure there are lots of problems, in fact.
What I'm saying is that it's facile to observe that women in tech are more often described as being aggressive and to assume that this is a problem with how people are described; it would be equally consistent with the evidence to conclude that the problem is one of non-aggressive women never getting hired into this field.
Your logic is inconsistent. This author is applying real data to an assertion. That assertion is backed up not only by my own experiences, but to the dozens if not hundreds or thousands of women sharing this all over social media with something akin to "see, this happens to all of us."
The author makes no such blanket statement as you suggest--rather she shows the results of her own study. What's facile is not her conclusions but rather the non data backed assertions you claim. You are the one asserting she extends her findings beyond her own sphere. to quote the author:
"I only have the data I have. I don’t know whether women were simply more willing to submit reviews that include critical language, or whether men removed language from their review documents before submitting. But the directional indication is striking and calls for further investigation by managers and HR departments. At most mid-size or large tech companies, HR leaders supervise review scores to uncover and correct patterns of systematic bias. This is a call to action to bring the same rigor to the review language itself."
The author makes no such blanket statement as you suggest--rather she shows the results of her own study. What's facile is not her conclusions but rather the non data backed assertions you claim. You are the one asserting she extends her findings beyond her own sphere. to quote the author:
"I only have the data I have. I don’t know whether women were simply more willing to submit reviews that include critical language, or whether men removed language from their review documents before submitting. But the directional indication is striking and calls for further investigation by managers and HR departments. At most mid-size or large tech companies, HR leaders supervise review scores to uncover and correct patterns of systematic bias. This is a call to action to bring the same rigor to the review language itself."
Maybe I'm misinterpreting what the author wrote, but it seems clear to me that, having identified a statistical anomaly, she is assuming one explanation -- that there is a problem with the review process -- and ignoring other potential explanations (e.g., a bias in hiring which results in non-aggressive women never being hired and thus never being reviewed).
> having identified a statistical anomaly, she is assuming one explanation
That is where you are going askew. There are two ways to derive knowledge from data. A) Start with a theory. Generate falsifiable hypothesis. Perform observation that validates or contradicts hypothesis. B) Start with statistical anomaly. Generate hypothesis (or hypotheses). Validate with more data.
Your objection assumes that the author took path B. She did not, she took path A: Starting with the hypothesis, and looking for confirming or disconfirming data.
The fact that there are other possible explanations is a valid point, but what you are doing is starting down path B, with your starting point being half-way through someone else's path A. It's a valid point, but it's not really an objection. In this approach, it would be a next-step, not something expected at this stage.
Sidenote: Most programmer-types seem to implicitly assume path B when reading research results. I assume this is because path B is how data-mining and machine learning work. Historically, path A is the more common approach, and is closer to the definition of the scientific method. Path B has only opened up recently, since data-collection has become more ubiquitous.
That is where you are going askew. There are two ways to derive knowledge from data. A) Start with a theory. Generate falsifiable hypothesis. Perform observation that validates or contradicts hypothesis. B) Start with statistical anomaly. Generate hypothesis (or hypotheses). Validate with more data.
Your objection assumes that the author took path B. She did not, she took path A: Starting with the hypothesis, and looking for confirming or disconfirming data.
The fact that there are other possible explanations is a valid point, but what you are doing is starting down path B, with your starting point being half-way through someone else's path A. It's a valid point, but it's not really an objection. In this approach, it would be a next-step, not something expected at this stage.
Sidenote: Most programmer-types seem to implicitly assume path B when reading research results. I assume this is because path B is how data-mining and machine learning work. Historically, path A is the more common approach, and is closer to the definition of the scientific method. Path B has only opened up recently, since data-collection has become more ubiquitous.
I do think you are misinterpreting the author.
1. She states very clearly in the last line: this is a call to action to review the language in reviews for for bias, not just the scores.
2. I can see you and others here very willing to accept the possibility that women just are more aggressive and that worries me about potential bias far more than this study does. Do you see that in yourself? To be fair to you, I see in myself the bias to believe what I read here because it is absolutely consistent with my experience. If you do too (i.e. you believe women in tech/business are somehow more aggressive, out of gender norm, etc) then that is a perfect reason to step back for a minute and examine your perceptions.
3. As you state above, non aggressive women never getting hired--one possible reason could be, as others have stated is that non aggressive women do not have the emotional or financial resources to withstand the cultural assault of doing something outside of gender norms. Do you see why that's a problem? Why the stereotypes of behavior in tech/business that are predominantly male are so damaging? And why it would be so important to look at the language used here?
4. Honestly, now, are you not struck by the difference in tone in those reviews? Or do you truly believe the women's words were "deserved?" because that's the fundamental question that the author asks us to consider.
1. She states very clearly in the last line: this is a call to action to review the language in reviews for for bias, not just the scores.
2. I can see you and others here very willing to accept the possibility that women just are more aggressive and that worries me about potential bias far more than this study does. Do you see that in yourself? To be fair to you, I see in myself the bias to believe what I read here because it is absolutely consistent with my experience. If you do too (i.e. you believe women in tech/business are somehow more aggressive, out of gender norm, etc) then that is a perfect reason to step back for a minute and examine your perceptions.
3. As you state above, non aggressive women never getting hired--one possible reason could be, as others have stated is that non aggressive women do not have the emotional or financial resources to withstand the cultural assault of doing something outside of gender norms. Do you see why that's a problem? Why the stereotypes of behavior in tech/business that are predominantly male are so damaging? And why it would be so important to look at the language used here?
4. Honestly, now, are you not struck by the difference in tone in those reviews? Or do you truly believe the women's words were "deserved?" because that's the fundamental question that the author asks us to consider.
1. She states very clearly in the last line: this is a call to action to review the language in reviews for for bias, not just the scores.
Right, and I'm taking that as saying "HR should look for bias in the language used in reviews because I think they will find it".
2. I can see you and others here very willing to accept the possibility that women just are more aggressive and that worries me about potential bias far more than this study does. Do you see that in yourself?
Do I think that women in general are more aggressive than men? No. Do I think that women in tech fields are more aggressive than men? I don't have enough evidence to form an opinion about this, but given the challenges which women must overcome in order to succeed in tech fields, I think it's entirely possible that the less-aggressive women tend to get filtered out.
3. As you state above, non aggressive women never getting hired--one possible reason could be, as others have stated is that non aggressive women do not have the emotional or financial resources to withstand the cultural assault of doing something outside of gender norms. Do you see why that's a problem? Why the stereotypes of behavior in tech/business that are predominantly male are so damaging? And why it would be so important to look at the language used here?
Absolutely. I'm not willing to jump to the conclusion that the reviews are wrong, though.
are you not struck by the difference in tone in those reviews? Or do you truly believe the women's words were "deserved?"
Given that I do not know the men or women in question, I am unable to form an opinion about whether the adjectives used to describe members of either gender were accurate.
Right, and I'm taking that as saying "HR should look for bias in the language used in reviews because I think they will find it".
2. I can see you and others here very willing to accept the possibility that women just are more aggressive and that worries me about potential bias far more than this study does. Do you see that in yourself?
Do I think that women in general are more aggressive than men? No. Do I think that women in tech fields are more aggressive than men? I don't have enough evidence to form an opinion about this, but given the challenges which women must overcome in order to succeed in tech fields, I think it's entirely possible that the less-aggressive women tend to get filtered out.
3. As you state above, non aggressive women never getting hired--one possible reason could be, as others have stated is that non aggressive women do not have the emotional or financial resources to withstand the cultural assault of doing something outside of gender norms. Do you see why that's a problem? Why the stereotypes of behavior in tech/business that are predominantly male are so damaging? And why it would be so important to look at the language used here?
Absolutely. I'm not willing to jump to the conclusion that the reviews are wrong, though.
are you not struck by the difference in tone in those reviews? Or do you truly believe the women's words were "deserved?"
Given that I do not know the men or women in question, I am unable to form an opinion about whether the adjectives used to describe members of either gender were accurate.
I can see where you are coming from. I understand that innate perception, no matter how well intentioned, is a really hard thing to observe and think critically about in ourselves.
I just want to ask you about the last line. you truly, truly have NO opinion about what you read there? you don't think there's anything amiss or disturbing at all about the apparent pattern? I confess based on that and your answer to #3, you sound a bit, well like a robot--someone so deeply embedded in your own logic that you cannot see the larger picture. I don't think you're a hopeless misogynist at all, but I do think you might be missing something.
I just want to ask you about the last line. you truly, truly have NO opinion about what you read there? you don't think there's anything amiss or disturbing at all about the apparent pattern? I confess based on that and your answer to #3, you sound a bit, well like a robot--someone so deeply embedded in your own logic that you cannot see the larger picture. I don't think you're a hopeless misogynist at all, but I do think you might be missing something.
I believe that if I have a bias, it is that I assume good faith. But I don't think this is an incorrect bias to have, given that my experience has been that most people act in good faith most of the time.
I just want to ask you about the last line. you truly, truly have NO opinion about what you read there?
About whether the individual reviews are accurate? Only that it is most likely that the reviewers were not deliberately skewing their reviews in any direction.
you don't think there's anything amiss or disturbing at all about the apparent pattern?
Much to the contrary, it is very clear that there is a problem. What concerns me most is the possibility that the reviews are completely accurate -- since that would indicate that there is a large pool of less-aggressive women who are being overlooked during hiring or discouraged from entering the field.
you sound a bit, well like a robot
A past girlfriend told me that I reminded her of ST:TNG's Commander Data. I decided to take this as a compliment. I don't think she meant it as one.
I just want to ask you about the last line. you truly, truly have NO opinion about what you read there?
About whether the individual reviews are accurate? Only that it is most likely that the reviewers were not deliberately skewing their reviews in any direction.
you don't think there's anything amiss or disturbing at all about the apparent pattern?
Much to the contrary, it is very clear that there is a problem. What concerns me most is the possibility that the reviews are completely accurate -- since that would indicate that there is a large pool of less-aggressive women who are being overlooked during hiring or discouraged from entering the field.
you sound a bit, well like a robot
A past girlfriend told me that I reminded her of ST:TNG's Commander Data. I decided to take this as a compliment. I don't think she meant it as one.
Please be careful brandishing intellectual superweapons.
>> And one could make the argument that the sample of men was also biased--towards men who liked tech.
Sure. I think the implicit assumption is that "men in tech" is a more representative sample of "men" than "women in tech" is for "women".
Sure. I think the implicit assumption is that "men in tech" is a more representative sample of "men" than "women in tech" is for "women".
cperciva did not attack the methodology at all, which would be clear if you'd thoroughly read the first sentence. He didn't really say anything that disagreed with it at all, but rather put forward a hypothesis explaining the data therein. Said hypothesis implicitly acknowledges that it is harder for women to get into the workplace. But because his phrasing happened to include the phrase "sampling bias", you got angry and apparently stopped reading, missing the forest for the trees.
I find it telling that you jump right into assigning me an emotional response for countering his logic with my own. Do you often accuse women of being too emotional? Or too aggressive? I can tell you that I have a male named account on hacker news and it never, ever gets called too angry, or aggressive, or emotional. Try it sometime, as a woman. It's most instructive.
I'm not sure I've ever called anyone too aggressive or too emotional. I can say that you are far from the first commenter I've castigated for completely missing the point. You're still doing it. No one in this subthread is disputing that there is an issue wrt women in tech. Whatever the other evidence, there's enough smoke to indicate a fire. I was going to ask for details on your male-named account, but realized I believe you, and it doesn't change the situation.
As for deducing an emotional response, your logic was obviously[] (and self-destructively) flawed, and the usual cause for that is some sort of emotional involvement. This is completely universal. I hardly needed to know, in addition, that this an emotionally sensitive topic. Which it is, what with everyone being accused of something.
While I couldn't vouch for my specific language in previous posts, this is not the first time I've done this and I'm guessing it was mostly men before. I'll try to work on bthem more evenhanded, when it comes up; I don't like a perceptual bias any more than you do.
[] For reasons I won't bother repeating. I'll just note that you didn't bother refuting any of them and went straight for the personal attack.
As for deducing an emotional response, your logic was obviously[] (and self-destructively) flawed, and the usual cause for that is some sort of emotional involvement. This is completely universal. I hardly needed to know, in addition, that this an emotionally sensitive topic. Which it is, what with everyone being accused of something.
While I couldn't vouch for my specific language in previous posts, this is not the first time I've done this and I'm guessing it was mostly men before. I'll try to work on bthem more evenhanded, when it comes up; I don't like a perceptual bias any more than you do.
[] For reasons I won't bother repeating. I'll just note that you didn't bother refuting any of them and went straight for the personal attack.
>I can tell you that I have a male named account on hacker news and it never, ever gets called too angry, or aggressive, or emotional.
I'm not being sarcastic or facetious - this is a very enlightning statement and I almost cannot believe my own bias. To me your comments have sounded aggressive and emotional and it may just be my subconcious had seen your account name and biased my conscious assessment. So please forgive this bias, I didn't realize it ever existed! (for what it's worth I have historically thought myself to be logical, rational, and understanding of my own bias in most circumstances!)
I'm not being sarcastic or facetious - this is a very enlightning statement and I almost cannot believe my own bias. To me your comments have sounded aggressive and emotional and it may just be my subconcious had seen your account name and biased my conscious assessment. So please forgive this bias, I didn't realize it ever existed! (for what it's worth I have historically thought myself to be logical, rational, and understanding of my own bias in most circumstances!)
I also thought the OP "sounded aggressive and emotional", and it was until she brought up the issue of a commenter's gender that I notice the OP's own gender (assuming "Melinda" is female, of course).
I'm male BTW.
I'm male BTW.
I respect your ability to admit that and share it with people here. Truly isn't that the way we can all get better at understanding each other, to walk in each other's shoes?
hats off to you.
hats off to you.
Interestingly, although the op uses the term 'sampling bias' which is usually used to discredit a study, the actual content of their comment doesn't seem intended to do so.
What they're talking about is not a sampling bias. If more aggressive women are hired than not, that's not a sampling bias... those women are representative of the population as it exists.
It's only a sampling bias, if say the study somehow selected individuals from the population in a non-random fashion, so as to overemphasize one particular trait.
What they're talking about is not a sampling bias. If more aggressive women are hired than not, that's not a sampling bias... those women are representative of the population as it exists.
It's only a sampling bias, if say the study somehow selected individuals from the population in a non-random fashion, so as to overemphasize one particular trait.
Whether it's a sampling bias or not depends on the conclusion you're trying to draw. I agree that there is no reason to think that the women considered were unrepresentative of women in tech; my point was that women in tech may not be a representative sample of the gender as a whole.
That's true, but this is a study specifically about women in high positions in the tech field. I'm not sure its meant to be indicative of women in general, just as studies on male CEOs (e.g. the ones that claim CEOs are more sociopathic) wouldn't be meant to say anything about men in general.
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.
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.
> 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.
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.
The question is the problem vs a problem. This research uncovers a problem, it does not explicitly state what the problem is. What problem this research found is what people are questioning.
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.
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.
Exactly what part here is misrepresented?
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.
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.
The point is that you can't know whether they're rated differently (by different criteria) or actually different.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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I think this is an outgrowth of our general social tendency to judge men by what they do ("he works at a hedge fund!") and women by what they're like ("she's really sweet!").
I found this paragraph in particular interesting:
> Words like bossy, abrasive, strident, and aggressive are used to describe women’s behaviors when they lead . . . . Among these words, only aggressive shows up in men’s reviews at all. It shows up three times, twice with an exhortation to be more of it.
My current boss told me after I got hired that he liked me at my interview because I came across as aggressive. It's a personality trait that works great for men, because we're given a wide latitude between "aggressive behavior" and "abrasive" behavior. To a certain extent, we correlate a certain level of aggressiveness, credit-taking, and talking over others with leadership potential. But it seems for women, such behavior can result in being told: "Sometimes you need to step back to let others shine."
I found this paragraph in particular interesting:
> Words like bossy, abrasive, strident, and aggressive are used to describe women’s behaviors when they lead . . . . Among these words, only aggressive shows up in men’s reviews at all. It shows up three times, twice with an exhortation to be more of it.
My current boss told me after I got hired that he liked me at my interview because I came across as aggressive. It's a personality trait that works great for men, because we're given a wide latitude between "aggressive behavior" and "abrasive" behavior. To a certain extent, we correlate a certain level of aggressiveness, credit-taking, and talking over others with leadership potential. But it seems for women, such behavior can result in being told: "Sometimes you need to step back to let others shine."
But if you remove the other advantages/disadvantages of being female/male, and just ask someone: "Would you rather be judged on your profession/career or personality/behavior?", I think most rational people would pick the latter.
I have a pet theory that the reason that women (as well as non-traditionally-masculine men) are considered bossy, while other men are considered "go-getters" is due to a lack of the threat of violence. Not that a type-A guy is going to assault you if you don't capitulate to their authority. More that there is a perceived or possible threat.
In contrast to women who would be considered bossy or abrasive because they don't "back up" their claims to authority. I suppose that there is often a feeling of resentment that society/culture/custom is taking the place of that threat.
Again, all supposition and musing on my part. Probably much better articulated by someone writing on the subject 50 years ago!
In contrast to women who would be considered bossy or abrasive because they don't "back up" their claims to authority. I suppose that there is often a feeling of resentment that society/culture/custom is taking the place of that threat.
Again, all supposition and musing on my part. Probably much better articulated by someone writing on the subject 50 years ago!
I've never heard this but the idea seems compelling!
Another way to describe it might be as a mismatch between the pecking order according to our simian brains and what's on the org chart. I.e. we don't resent bossy behavior by someone we perceive as a dominant alpha, but bristle when it's someone we see as below us in the "pack".
Another way to describe it might be as a mismatch between the pecking order according to our simian brains and what's on the org chart. I.e. we don't resent bossy behavior by someone we perceive as a dominant alpha, but bristle when it's someone we see as below us in the "pack".
It also seems to tangentially make sense with the bias against "smaller" men in leadership positions.
This is an interesting point. We often observe a backlash against those who claim authority but don't deserve it (whether from being new, smaller, weaker, less skilled--lower on whatever status criteria is established in the group). In the case with masculine men, there might be a subconscious acceptance of their claim to authority, whereas with a woman there is a subconscious resentment towards their claim.
Right, but to be clear: I don't believe that only masculine men deserve authority. I think our species' slow evolution from violence as the single source of authority is possibly the most hopeful development in our history.
Is it possible that professional women are more abrasive than men in aggregate? I am not saying that is the case, only that it is another hypothesis from the data. If that was the case and I had to guess a reason, it would be that groups with more power insecurity tend to overcompensate in other areas.
Another explanation could be industry. More women work in Fashion and marketing, which have generally more dramatic environments.
Another explanation could be industry. More women work in Fashion and marketing, which have generally more dramatic environments.
This could also be the result of misapplying articles such as this one (http://www.rolereboot.org/culture-and-politics/details/2014-...) where women are taught to be dominant, and say things like "Stop interrupting me", and "I just said that". [Said article was making the rounds on Facebook among my professional female friends recently.]
Topics tend to be rehashed quite a lot in discussion, and sometimes people interrupt one another. It is entirely plausible that this probably affects women more than men. But if someone compensates by saying things like "I just said that", or "Stop interrupting me.", it is not surprising that they would get reviews that label them as abrasive; whereas they might just be trying to be more assertive than usual by following this sort of advice too literally.
Solutions? Perhaps a more holistic approach, where all parties involved are reminded that women might be less assertive, or be dominated in the conversation, and take steps to mitigate this. (Or possibly also being reminded that speaking is not
Topics tend to be rehashed quite a lot in discussion, and sometimes people interrupt one another. It is entirely plausible that this probably affects women more than men. But if someone compensates by saying things like "I just said that", or "Stop interrupting me.", it is not surprising that they would get reviews that label them as abrasive; whereas they might just be trying to be more assertive than usual by following this sort of advice too literally.
Solutions? Perhaps a more holistic approach, where all parties involved are reminded that women might be less assertive, or be dominated in the conversation, and take steps to mitigate this. (Or possibly also being reminded that speaking is not
It's possible. It's equally possible that there's a lot of men who like to dish it out but can't take it.I used to do a lot of work with hedge funds and the amount of preening and effort invested in maintaining the pecking order (in an all-male environment) was just ridiculous.
"More women work in Fashion and marketing, which have generally more dramatic environments."
Do you have data on this?
Do you have data on this?
Data point: My girlfriend is a tech designer who's worked at Guess, Hot Topic, and a slew of smaller companies. She absolutely loathes the working environment because of the drama and bitterly regrets getting into the industry. She's considering going into customer service in a call center(!) (a 50%+ pay cut) because the work environments are so stressful in the fashion industry. She explicitly blames it on the gender balance being so female-dominated.
So, anecdotal. Got it.
But let's say we accept it. We still need data on the "relative drama" of male-dominated industries. And considering this includes industries like finance, law and policing, I think you might be surprised what the answer turns out to be.
But let's say we accept it. We still need data on the "relative drama" of male-dominated industries. And considering this includes industries like finance, law and policing, I think you might be surprised what the answer turns out to be.
Yes. She may just be seeing the grass as greener on the other side. There's been drama to an absurd degree between men at places that I've worked.
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It's possible, but the likelihood is so low some might wonder why you're bringing that possibility up rather than discuss the much more likely alternative and how we can fix it.
Also; "I asked men and women in tech if they would be willing to share their reviews for a study and didn’t stipulate anything else."
Also; "I asked men and women in tech if they would be willing to share their reviews for a study and didn’t stipulate anything else."
Why do you think the likelihood is very small?
Has there been research?
Has there been research?
Groups who are or expect to be treated differently will behave differently. Groups who are specifically taught to behave differently will also behave differently.
Are both of those really that unlikely?
We have arguments here all the time about perceived vs actual sexism or the effects of cultural gender norms, and have female-specific business self-help books.
Are both of those really that unlikely?
We have arguments here all the time about perceived vs actual sexism or the effects of cultural gender norms, and have female-specific business self-help books.
I think there's certainly a likelihood that men and women are different, and that not every perceived difference is sexism.
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This surprises anyone? I was engaged to a high achieving woman for a period of time. I loved her, but damn, if I had to work with her, I wouldn't put up with her personality. Very aggressive, pushy, and intolerant, to my mind. Very quick to take offense at the slightest provocation, whether offense was intended, or merely the result of ignorance or incompetence.
Then again, I'm a libertarian-minded introvert, so I basically just want to let other people do their thing and have them leave me alone...
On the whole, I see the adversarial nature of gender politics that is often pushed as profoundly dysfunctional. Men and women are not the same. Each gender is better at some things and worse at others, on average. Men tend to have more variance, so you see more male geniuses and male idiots (the tails on the bell-curve are bigger), where women tend to cluster towards the mean more strongly. If we could just accept this, and spend our time trying to be happy, rather than demonizing each other, the world would be a better place.
On the whole, I see the adversarial nature of gender politics that is often pushed as profoundly dysfunctional. Men and women are not the same. Each gender is better at some things and worse at others, on average. Men tend to have more variance, so you see more male geniuses and male idiots (the tails on the bell-curve are bigger), where women tend to cluster towards the mean more strongly. If we could just accept this, and spend our time trying to be happy, rather than demonizing each other, the world would be a better place.
I'm not surprised by this, but I am surprised that the author didn't mention her past research on this topic. Her shock at the "discovery" seems a little disingenuous.
http://languagelog.ldc.upenn.edu/nll/?p=13513
http://languagelog.ldc.upenn.edu/nll/?p=13513
The down vote is interesting since I actually agree with her primary research. Women should interrupt more. I've said as much when doing reviews myself.
Had I downvoted (I didn't) it would have been because I didn't see any shock in her article, real or feigned. It was clear that the effect she found was the one she was looking for.
I think it was really this statement which made me crinkle my nose.
"As a woman in tech who has been called all of these things before, there is some validation in confirming with data that the pattern is real. But as a leader in tech, I’m aghast at how closely under our noses we let this live."
Her past research would seem to suggest that this finding was all but assured. But to be fair, that could just be my reading if it. I have a lot of respect for Kieran's work, so that also has something to do with it.
"As a woman in tech who has been called all of these things before, there is some validation in confirming with data that the pattern is real. But as a leader in tech, I’m aghast at how closely under our noses we let this live."
Her past research would seem to suggest that this finding was all but assured. But to be fair, that could just be my reading if it. I have a lot of respect for Kieran's work, so that also has something to do with it.
It's very hard for us to overlook sexual dimorphism in everything we do, and it's not even clear we should. It's however very trendy nowadays to pretend that it doesn't exist, probably for political correctness reasons.
it's not that women are more aggressive, it's that they're perceived as more aggressive relative to expectations (by both male & female managers).
also, it's much more acceptable to challenge a woman's authority than it is a man's. when all you want to do is get things done, this social norm slows you down. you have to explain, persuade, and butter up your peers more as a woman. this is just one way that these subtle biases can lead to divergent outcomes (seeming to be less effective and successful in this case).
also, it's much more acceptable to challenge a woman's authority than it is a man's. when all you want to do is get things done, this social norm slows you down. you have to explain, persuade, and butter up your peers more as a woman. this is just one way that these subtle biases can lead to divergent outcomes (seeming to be less effective and successful in this case).
That may be so, but it unfortunately can't be determined from this study.
Let me understand: you think nothing of value can be determined from this study even though my entire newsfeed on facebook is full of my friends in all industries sharing it as exactly in line with their experiences?
Yes.
You have a sampling bias in the types of people you associate. Facebook applies a filter to posts which selects for things that are popular with a wide swath of your friends and which support your political/social views (as guessed by their profiling tools).
That something blows up with your friends on Facebook is usually a better indicator that it's polarizing drivel than that it's a well thought out, impactful study, since that's what the machines (essentially) optimize for.
You have a sampling bias in the types of people you associate. Facebook applies a filter to posts which selects for things that are popular with a wide swath of your friends and which support your political/social views (as guessed by their profiling tools).
That something blows up with your friends on Facebook is usually a better indicator that it's polarizing drivel than that it's a well thought out, impactful study, since that's what the machines (essentially) optimize for.
Polarizing Drivel. Wow. That's pretty harsh.
The author posts the data, then calls for further study. Isn't that the very basis of science? She admits fully its potential for inaccuracies and wonders aloud about its flaws. Isn't that what peer review is for? The women in tech say it feels true, and it matches their experience. So why isn't the Hacker News Community demanding a peer reviewed study and supporting it, and financing it? Why does it instead choose to ignore its substance, and tear down its conclusions based on its already admitted flaws?
Truly, the persistent and relentless attempts on the part of some Hacker News denizens to discredit any science about bias in technology is disappointing. Any and all attempts to quantify the problem are met with such resistance that it belies the community's own assertions about its objectivity.
The author posts the data, then calls for further study. Isn't that the very basis of science? She admits fully its potential for inaccuracies and wonders aloud about its flaws. Isn't that what peer review is for? The women in tech say it feels true, and it matches their experience. So why isn't the Hacker News Community demanding a peer reviewed study and supporting it, and financing it? Why does it instead choose to ignore its substance, and tear down its conclusions based on its already admitted flaws?
Truly, the persistent and relentless attempts on the part of some Hacker News denizens to discredit any science about bias in technology is disappointing. Any and all attempts to quantify the problem are met with such resistance that it belies the community's own assertions about its objectivity.
Looking at the data, I don't think the author did anything with it than see initial numbers matched her feelings, and then called on people to undertake a massive, actual study because she just know this is it.
I certainly think that there are problems with gender in society in virtually every place we could examine, and that we have a long way to go before things are what anyone could call ideal.
I just have trouble with a lot of the statistics used in these discussions, and find that they're very often 20+ years out of date (ie, from or before 1994-1995), don't control for confounding influences, make misleading comparisons, etc.
I would take posts like this much more seriously if she posted the dataset, but I'm not sure how she could do this without revealing personal details or editing the text (which likely would bias the choice of recipients further, or could introduce a new bias). I would even settle for the details of how she did the bucketing, correlations between words and numbers of entries per person, etc.
The short answer to why I think that this article isn't a real source of data is that the study in it has about the statistical power of just asking everyone who's a friend of a friend on Facebook for people with a moderate number of friends.
Everyone already knows that there's a problem with gender in tech. This article does nothing about saying where it is and doesn't really contribute anything to the topic.
I certainly think that there are problems with gender in society in virtually every place we could examine, and that we have a long way to go before things are what anyone could call ideal.
I just have trouble with a lot of the statistics used in these discussions, and find that they're very often 20+ years out of date (ie, from or before 1994-1995), don't control for confounding influences, make misleading comparisons, etc.
I would take posts like this much more seriously if she posted the dataset, but I'm not sure how she could do this without revealing personal details or editing the text (which likely would bias the choice of recipients further, or could introduce a new bias). I would even settle for the details of how she did the bucketing, correlations between words and numbers of entries per person, etc.
The short answer to why I think that this article isn't a real source of data is that the study in it has about the statistical power of just asking everyone who's a friend of a friend on Facebook for people with a moderate number of friends.
Everyone already knows that there's a problem with gender in tech. This article does nothing about saying where it is and doesn't really contribute anything to the topic.
There is almost no science in studies like this. There are so many variables, that you'd need to collect hundreds of thousands of data points to narrow down the influence on just a couple of variables... and even then, you can't be sure you've found something significant and meaningful. To do science, you need controlled experiments, and these are practically impossible to do with people. Even the well-known psychological "experiments" have been disputed in the recent years [1] [2].
[1]: parapsychology experiments cannot be disproved http://slatestarcodex.com/2014/04/28/the-control-group-is-ou...
[2]: "The Stanford Prison Experiment was flawed" https://news.ycombinator.com/item?id=8073748
[1]: parapsychology experiments cannot be disproved http://slatestarcodex.com/2014/04/28/the-control-group-is-ou...
[2]: "The Stanford Prison Experiment was flawed" https://news.ycombinator.com/item?id=8073748
I don't think nothing of value can be determined from the study, but I do think what clairity said can't be determined from the study. It really is entirely possible, going strictly by the findings here, that ornery women are overrepresented in this area in much the same way that upper-class white women are underrepresented among convicts.
Your experience may tell you different, and your experience may very well be right — I am definitely not qualified to say either way. I was just bemoaning that what many people seem to want to get out of this study — whether there's a difference in the way men and women are perceived in essentially identical situations — isn't actually in this study.
Your experience may tell you different, and your experience may very well be right — I am definitely not qualified to say either way. I was just bemoaning that what many people seem to want to get out of this study — whether there's a difference in the way men and women are perceived in essentially identical situations — isn't actually in this study.
one study can (almost) never be conclusive but hopefully you realize that your alternative hypothesis is less likely given the data presented.
your desire to espouse that alternative hypothesis is another subtle form of bias that discounts an otherwise uncomfortable potential conclusion (and it's uncomfortable for both genders). which is not to put it all on you because many people (all?) carry this bias to some extent. it would really help if folks were simply open to the likelihood of bias running through us without feeling like we're all bad people because of it.
(this is the same subtle bias that urges media to "balance" the climate change issue by giving the deniers equal airtime. sure, the conclusion that climate change is due to people has a (very) small chance of being wrong, but let's spend our energy finding solutions, not trying to poke little holes in what is likely a real and serious problem.)
your desire to espouse that alternative hypothesis is another subtle form of bias that discounts an otherwise uncomfortable potential conclusion (and it's uncomfortable for both genders). which is not to put it all on you because many people (all?) carry this bias to some extent. it would really help if folks were simply open to the likelihood of bias running through us without feeling like we're all bad people because of it.
(this is the same subtle bias that urges media to "balance" the climate change issue by giving the deniers equal airtime. sure, the conclusion that climate change is due to people has a (very) small chance of being wrong, but let's spend our energy finding solutions, not trying to poke little holes in what is likely a real and serious problem.)
> one study can (almost) never be conclusive but hopefully you realize that your alternative hypothesis is less likely given the data presented.
I might be setting myself up to look dumb, but I don't realize that. Obviously there's something causing the phenomenon, but as far as I can tell, the data does not contain any good clues as to what it is. It could be that people perceive women's actions differently from men's. It could be that the women in question actually are more abrasive in general than their male peers and the people's comments are an accurate reflection of reality. It could be that people perceive abrasiveness equally, but they are more likely to complain about it from women because they have lower expectations of men.
I'm not espousing any of these ideas — and I'm definitely not saying your explanation is wrong. Like I said, I don't feel qualified to support any hypothesis here. But I don't see how this study supports any hypothesis more than the others. Where do you see it?
I might be setting myself up to look dumb, but I don't realize that. Obviously there's something causing the phenomenon, but as far as I can tell, the data does not contain any good clues as to what it is. It could be that people perceive women's actions differently from men's. It could be that the women in question actually are more abrasive in general than their male peers and the people's comments are an accurate reflection of reality. It could be that people perceive abrasiveness equally, but they are more likely to complain about it from women because they have lower expectations of men.
I'm not espousing any of these ideas — and I'm definitely not saying your explanation is wrong. Like I said, I don't feel qualified to support any hypothesis here. But I don't see how this study supports any hypothesis more than the others. Where do you see it?
yes, i wasn't really commenting on the study (the conclusions of which are not surprising) so much as trying to extend the discussion since folks may not discern the subtle underlying mechanisms at work.
it's like staring at pages of math trying to find that off-by-one error. it's much easier to see when it's pointed out.
it's like staring at pages of math trying to find that off-by-one error. it's much easier to see when it's pointed out.
The manager’s gender isn’t a factor.
So what's the best way to rearrange corporate structures so that doing well in business doesn't require traits that don't match our cultural ideal for what women should be like? Or would changing cultural ideals be easier (maybe find a way to get hollywood on board)?
I guess I'm assuming here that "I figured only strong performers would be willing to share" is correct, and selected for mostly people who do behave in a mostly-ideal fashion for business success.
So what's the best way to rearrange corporate structures so that doing well in business doesn't require traits that don't match our cultural ideal for what women should be like? Or would changing cultural ideals be easier (maybe find a way to get hollywood on board)?
I guess I'm assuming here that "I figured only strong performers would be willing to share" is correct, and selected for mostly people who do behave in a mostly-ideal fashion for business success.
At my previous job, I had both male and female co workers who were bossy and abrasive.
I don't know if that means I transcended gender or just needed to find a better place to work.
I don't know if that means I transcended gender or just needed to find a better place to work.
Men and women get different from of criticism. Our current culture is to judge men by what they do, women by their person. This article simply include an other example of a rather well established concept.
It would be kind of fun to see what happen if the reviewer intentionally reversed this and judged women solely from what they accomplish, and men on their personality with a token "The work ultimately went well". The resulting culture shock and mixed signals would be an interesting pattern to observe.
An other kind of interesting test would be a dating site that write the profiles for its clients. If they wrote female profile that only focused on job, earning, and skills, and a male profiles that only describe the person personality and looks, would the clients be happy when they got to read their own profiles?
It would be kind of fun to see what happen if the reviewer intentionally reversed this and judged women solely from what they accomplish, and men on their personality with a token "The work ultimately went well". The resulting culture shock and mixed signals would be an interesting pattern to observe.
An other kind of interesting test would be a dating site that write the profiles for its clients. If they wrote female profile that only focused on job, earning, and skills, and a male profiles that only describe the person personality and looks, would the clients be happy when they got to read their own profiles?
I am a bit surprised, the review process I participate in would probably automatically reject the review; there is a legal check and one other whose name escapes me done with software that is really restrictive on words you can use. So I doubt these would arise in any company which has a robust legal department, you just don't do that anymore especially in writing. Mandatory HR meetings, too many electronically signed HR type docs, and it all goes the same way - offend certain groups and your not going to receive any support.
Did you happen to notice the author's full name and workplace? And at startups where much of the more recent notorious and egregious behavior is happening, there is no such thing as a legal department, let alone a robust one.
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Url changed from http://m.fastcompany.com/3034895/strong-female-lead/the-one-..., which points to this.
i don't find this shocking
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.