r/science • u/[deleted] • Nov 19 '20
RETRACTED - Social Science [deleted by user]
[removed]
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u/DrMonkeyLady Nov 20 '20
One of the big problems with this paper is that it fails to address the fact that sexism is the likely cause of that major result...
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Nov 20 '20
Got a study on that?
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u/DrMonkeyLady Nov 20 '20
Are you kidding? There's dozens of studies on sexism in academia....
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u/toodrunktofuck Nov 20 '20
It's still on you to tie that premise into the argument you made above.
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u/DrMonkeyLady Nov 20 '20
It's common knowledge. And you can do your own googling for articles
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Nov 20 '20
It's common knowledge.
Is it? Looking at stipends and mentorship programs I would agree on there being a bias...
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u/DrMonkeyLady Nov 20 '20
The fact that there is sexism in academia is well established. And easy to google...
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Nov 20 '20
Go ahead then
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u/SuckinLemonz Nov 26 '20
Nobody should have to cite their sources when informing you the world is round. Insisting that they do is a method of degrading the conversation and impairing real discussion which is always built on the foundation of some accepted factual base.
The person you’re placing the ‘burden of proof’ on is attempting to have a conversation which requires the participants to have some baseline level of knowledge. They are not obligated to bring you up to speed on fundamentals.
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u/BioBit Nov 19 '20
For those not on Twitter: The twitter community has distilled this paper down to "women are bad mentors" and some are demanding the paper to be retracted because in the discussion the authors suggest:
Our gender-related findings suggest that current diversity policies promoting female–female mentorships, as well-intended as they may be, could hinder the careers of women who remain in academia in unexpected ways.
Female scientists, in fact, may benefit from opposite-gender mentorships in terms of their publication potential and impact throughout their post-mentorship careers.
Policy makers should thus revisit first and second order consequences of diversity policies while focusing not only on retaining women in science, but also on maximizing their long-term scientific impact.
More broadly, the goal of gender equity in science, regardless of the objective targeted, cannot, and should not be shouldered by senior female scientists alone, rather, it should be embraced by the scientific community as a whole. "
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u/SuckinLemonz Nov 20 '20
I’m not seeing a lot of good controls here. This seems to me like more of an examination of consequences deriving from longstanding bias and discrimination. It seems an overreach that the authors believe they’re in a position to make any recommendations towards best practices in promoting gender equality.
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u/myaltduh Nov 19 '20
It seems to me that assuming the analysis is valid (I really only skimmed the paper and am not qualified to asses study quality regardless), this paper's conclusions can square perfectly with the idea that there is systematic discrimination against women in science and that this is the main if not sole source of women's worse performance in several career metrics such as retention. To quote the paper's discussion:
One potential explanation could be that, historically, male scientists had enjoyed more privileges and access to resources than their female counterparts, and thus were able to provide more support to their protégés.
It makes sense to me that male scientist mentors, via their privilege, are more able to connect their students with career opportunities, research projects, etc. than their female colleagues. This in no way means that men are inherently better at being mentors, nor that having female role models isn't incredibly important.
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u/derpmeow Nov 20 '20
They are rather odious conclusions if you're a woman in STEM. (Obligatory "i don't speak for all women", but as you've noted twitter is afire so i don't think I'm alone.) Their data don't support their conclusions. They could have stopped short at "female-female mentorships publish less than cross-gender ones" and that would be that.1 But they presumed to make recommendations on policy in a way that implies women scientists would do better when a man is in the picture. That is pretty patronising. I present you a different possible conclusion - female-female mentorships publish less, therefore we should revisit the prevalence of gender bias by journal reviewers and editors. You could just as easily say that, though i think both statements - theirs and the e.g. i just gave - are "beyond the scope of this paper and warrant further research". But they chose what conclusion to draw, and that's why people are steamed about them having a sexist agenda.
- Though there are methodological criticisms also. Off the top of my head: they used genderize.io to determine gender without validating the tool's accuracy, 167/2000 is a 8.35% response rate which is kind of naff, there were no attempts to correct for confounders such as seniority or family status (how this paper got by without a CASE CONTROL DESIGN i don't know). But if they'd stopped short of their conclusions, we might be bitching about their methods but i guarantee people would not be this pissed off.
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Nov 19 '20 edited Nov 25 '20
[deleted]
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u/BioBit Nov 19 '20
I'm not sure how you got to such a conclusion from that paper... either way, you are wrong and your opinion is not backed by science.
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Nov 19 '20
You know it's unfortunate because most will jump to that same conclusion before even reading it :(
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u/whoishattorihanzo Nov 19 '20 edited Nov 21 '20
Isn’t there enough evidence of behavioral differences between sexes of basically every other species? But as humans we are really trying to push this whole man=woman thing when it’s just not anatomically or innately true. Yes, there are differences between sexes and therefore the interactions between each sex and amongst the same sex is going to be varied. Why does this come as a surprise and even go as far as to trigger a significant portion of the population? This is a statistical observation, if you let science influence your emotions then you are not a true believer (in good science).
Edit: All genders have the same capabilities but at the same time all are fundamentally different from one another.
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u/SuckinLemonz Nov 20 '20
Ah. Then may I assume your recommendation is that we should remove men from academia? After all, women have significantly higher acceptance rates, graduation rates, and test scores.
Or am I misunderstanding the intent of your absolutely absurd statement.
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u/desantoos Nov 20 '20
My Twitter feed is jammed with pissed off scientists. But having a look at the paper I find myself in a strange place: I think the methods and conclusions of the paper are ridiculous, but I also think plenty of the criticisms are not spot-on.
The major criticism is on these sentences of the conclusion:
As well as this corresponding sentence in the abstract:
Many are construing this paper to therefore say, "if you are woman and want to be an impactful scientist, you better be mentored by a man." And there is some weight to this, particularly if you read the peer-review comments, which show the reviewers arguing to the authors not to take such a sweeping definition of "mentorship" (which, for purposes of this paper, are essentially who is a coauthor on who's paper). However, critics ignore that the conclusion raised falls right after a paragraph that tries its best not to go that far:
No doubt that first sentence is a gross understatement and I can see how people may read this and say that it's not enough when they then force out the idea of male mentorships of women in research being superior.
However, I don't think the authors were trying to be sexist here. I think they jammed as hard as they could at the data they got and tried to make it fit the exact same conclusion they came to two years prior: In research, heterogeneity is better than homogeneity. In the earlier case, it was diversity of ethnicities that led to improvements in "impact"; in the latest, it is a diversity of genders.
The older paper on ethnicities hasn't been as roundly criticized. Perhaps it is due to its analysis being slightly more sophisticated, particularly in its statistical approaches. But there's no doubt that it also confirms to a current worldview and to preordained prejudices in the scientific community rather than challenges or contradicts it.
However, both manuscripts are highly flawed and while the authors have done great work elsewhere using their sophisticated modeling to show interesting things, in these two papers it is difficult to believe that the conclusions are right just based on the data alone. Both papers have a problem with regards to "impact." What is impact? According to our authors, a scientist's impact rests on the citations the papers that they publish have. This is flawed for a host of reasons. First, and most glaring, and I'm going to say this in all caps because it is beyond me why anybody would study citations as a measure of anything and I'm hoping maybe just one person who would do so reads this and then decides not to: REVIEW ARTICLES GET MORE CITATIONS, SO PEOPLE WHO WRITE MORE REVIEW ARTICLES WILL HAVE A LARGER IMPACT, WHICH TELLS US NOTHING ABOUT WHO THEY ARE. Review articles get around double the citations of a regular research Article. Consider the aformentioned paper on gender. The principal finding is that papers with seasoned authors get more citations. Consider that journals often invite seasoned authors to write review articles, and that older groups tend to have more researchers than younger groups, and you can see why that would obviously be the case. In fact, if you look at their data, it's quite easy to see how the impact could be just on that fact alone.
Second, people don't cite every prior paper that influenced their paper. The grad student or postdoc who writes the paper and the PI who edits and contributes to it often pick what they remember to be important. They often also have to deal with Reviewer 3 who frequently wants his three junk journal papers cited or else he won't agree that it should be accepted, and even if they don't have to deal with that person PIs regularly strategize to make sure every major potential reviewer is cited so that they don't hurt anyone's feelings. What I am saying here is that: people have no obligation to cite all influential work and they don't so citations end up being random. A PI might have that one prominent paper that everyone remembers and cites alongside two equally great equally influential papers that people skip over when they are trying to do the role call of people to cite, but it is often understood that citations are a jumping point to look at other papers and investigate a field further, not a comprehensive set of ingredients that go into the stew of a paper. To be plain: citations are often very random and so it's a bad idea to use them because there is so much noise and so much error.
Third, this paper weirdly takes the idea that we're all the administrators at a university and only consider some quant data of citations to determine whether someone has "impact." This may not be insulting when you're stating that ethnicity is a good thing because look at how that arbitrary number goes up, but it's certainly not going to look nice when you're evaluation now shows that women shouldn't be mentoring women. You are going to get people who will say, "but this woman taught me how to write, and these men who mentored me made my writing worse... isn't that change in character development just as important as citations?" Which is why deans and whatnot actually have to do their job and not just solely rely on citations. Maybe the authors could have talked to a few and looked at teaching evaluations and readability scores in writing they put out, anything to diversify what they consider impact than just citations. The fact that the authors took one unreliable metric and then used it wildly out of proportion to make broad sweeping conclusions is absolutely absurd and the peer reviewers don't do a good enough job hammering how poorly of a scientific approach is being done.
Fourth, none of this considers the people who are mentored and then go some place else. The MAJORITY of people who are mentored as graduate students leave academia. Rightfully so! There's lots of other jobs out there to do. So they're making these big sweeping statements about ethnicity and gender mentorship diversity being important when they don't measure the majority of the people affected.
These last two criticisms assume that citations is a good approach. Let's ignore the randomness and the narrowness of using citations to determine impact. There is a tremendous imbalance of power at universities, where top-tier ones get the vast number of citations while small ones get very little. What if Podunk U that puts out solid but mostly unread papers is less ethnically diverse, often because they're a smaller school that caters to the local population (whether in rural US or "rural" China (not big 2 cities) or elsewhere)? You can see how this imbalance in academia can lead to skewed results. It's likely similar in the gender study, where women are more prominent as younger faculty and so they're probably going to be more present at smaller schools, waiting to be scooped up by the MITs of the world. A second criticism is that maybe the peer reviewers of manuscripts are biased, or the people who write manuscripts are biased, and we end up disregarding women who should be cited more than they actually are.
The latest paper has additional flaws, but we need to start by tuning out papers that only use citations as an approach to measure the quality of a researcher.