Thoughts on rationalism and the rationalist community from a skeptical perspective. The author rejects rationality in the sense that he believes it isn't a logically coherent concept, that the larger rationalism community is insufficiently critical of it's beliefs and that ELIEZER YUDKOWSKY IS NOT THE TRUE CALIF.

Free Speech Slip and Slide

In the past I’ve written at length about my concern that the newly invigorated attitude that we must outlaw, or at least severely socially punish the speakers, racist/sexist/etc.. speech is a mistake. I have doubts about the efficacy of such punishments and believe that pushing racism adjacent views into a hidden underground where they fester and mutate1 creates more hate. However, the primary thrust of my concern was the usual slippery slope argument (importantly serious harms arise as soon as well-intentioned people start to fear that an epistemic mistake could land them in trouble). Unfortunately, evidence for a steep slippery plastic slope with extra soap arrived all too quickly.

Superiority of Western Culture

First we had this really stupid opinion piece that I would have guessed was written by a machine learning algorithm trained on 1980s era conservative values pieces if it had only mentioned crack (still managed a shout out to the pill for destroying our perfect 1950s society). Personally, I thought it was just as stupid this time around as I did in the late 80s and early 90s except these authors should have seen how that went and known better. However, as far as offensiveness goes it rates as a “kids these days…have no … always on their..” but somehow it has become the subject of accusations of racism and the subject of serious controversy (yes, that last article is written by a friend of the original author so take its slant with a grain of salt).

True, there is no credible effort to have the author fired from her position in the law school but it has generated enough outrage for students to get up in time to picket Wax’s class as racist and its not just some hasty people with signs. At least a non-trivial segment of the Penn campus left is willing to call this piece racist, sexist or otherwise suggest it isn’t just dumb and wrong but deserving of open moral scorn.

While one might try and charitably reconstruct some argument based on the text of the oped2 what is going on is what is always going on with accusations of racism/sexism/islamophobia etc.. Rather than parsing the literal content of a piece and asserting those claims amount to racism (or providing evidence that the author was being disingenuous) people decide to call something racist if it feels like the things racists would say. In this case there is no doubt this oped has that feel. Indeed, it hits many of the points that one would expect from a racist dog-whistle: glorification of European/western culture, suggestion that something associated with whites is superior, a nostalgic comparison to the 1950s, reference to some aspect of black culture the author disapproves of (“anti-“acting white” rap culture of inner-city blacks”) and even the obligatory focus on whites that have the traits you are criticizing.

The problem with taking this as grounds for accusations of racism is that it confuses being the sort of person whose strong affinity for traditionalism and reverence for long lived institutions and practices may make needed reform more difficult with actual racism. However, we are generally quite willing to let the earnest man who is such a strong believer in feminism that he frequently gives a piece of his mind to men who he views as pushing an aggressive male-centric approach on women and thereby does more to perpetuate the stereotype of women as unable to handle these situations than anyone he criticizes. This case is only different in that it is harder to imagine genuinely feeling that these old school conservative values are the secret to a better life and wanting to help minorities by sharing. Also in that often people who feel this way about morals and newfangled social innovations also feel this way about minorities but that’s just a stereotype.

Most importantly, it renders the standard for racism uselessly subjective. If it is no longer necessary to have overt animus or believe in some particular stereotype then it is insanely easy to apply the term to virtually anyone you want. Especially given that as the sphere of things that have been labeled racist expands fewer and fewer non-racists say anything in that sphere so just imagine the same dialog in 20 years about pieces supporting free speech. It would be something mostly racists talk about as a cover, anyone like me writing about it would explain that we believed in it for everyone (while detractors would point out that we kept focusing on the free speech of the racists as they don’t see it from the context in which that is the right place to make one’s stand), one could raise analogies to the contract rights arguments offered in the civil rights movement (yes its bad but the constitution…we just can’t do anything). The only thing this lacks is the subjective feel that comes from hearing lots of racists say something that sounds similar but we can’t cede to racists the power to decide what is and isn’t considered.

Also, as a practical matter this kind of use of the accusation of racism isn’t productive. The reason to use the term at all is to invoke our shared disapprobation of certain behaviors to change people’s behavior. Telling someone ‘suggesting that blacks only eat fried Chicken or look like Gorillas’ is racist usually results in an immediate change and the world is a better place but when you say that some vague thing about the gestalt I get from your article is racist doesn’t. If I were the author and was willing to sell out my views so I wouldn’t be racist how would I even know where to start?

Call these ideas out as stupid or even the kind of progress phobic thinking that perpetuates racism that’s great but its just not racism.

University of Tampa’s Impolitic Twitter Firing

Also, we have the University of Tampa firing a visiting professor for the following poorly considered and bumblinging inappropriate tweet

I dont believe in instant karma but this kinda feels like it for Texas. Hopefully this will help them realize the GOP doesnt care about them.

This is obviously just a case of someone not realizing how what he said would be taken in context. When he did he apologized. That should have been the end of it.

While at first glance one might feel that this isn’t really relevant to the broader picture at the moment. However, while it wasn’t exactly an academic paper this tweet is fundamentally nothing but an expression of a political sentiment. Indeed, suppose the author really believed this was some kind of divine vengeance on Texas for voting GOP. Surely that is core political-religious speech if anything is so its hard to see how this is anything but a direct attack on the idea that Professors get to comment on current events and broader social issues without fear of being fired for controversial views (assuming they don’t bear on their academic qualifications…mathematicians probably shouldn’t say $\omega$ and $2^\omega$ have the same cardinality).


We need room for people to make mistakes! Even mistakes about what to believe on controversial issues because only when people feel they won’t lose their jobs or be shunned if they get it wrong can they allow themselves to explore the issue and reach the right conclusions.

I know its really hard in these discussions to imagine any other perspective than your own but rarely is it the case that someone just wakes up out of the blue filled with hate and the desire to see another race suffer. Sure, sometimes the reasons are just visceral (your gang is white they are black) but in most cases there is some chain of thought and emotion that made every step they took seem reasonable so if you suspect the target of your criticism of simply reasonless hate you should probably reevaluate that view.

However, that is what makes the situation so dangerous as well. Given that even racists think they have good and sound justifications for their beliefs an atmosphere which imposes severe penalties for even minor infractions allows only one safe response: parrot back the official dogma.

But, if we are going to fix the remaining barriers and harms inflicted by problematic stereotypes and structural racism/sexism we need to find them in non-obvious places and that takes open speculation. We’ve picked all the low hanging fruit so more looking for white or male ‘perpetrators’ (if it could have been fixed easily that way we would have) we instead need to look at the less examined reservoirs of stereotypes such as members of the group themselves or the well-intentioned helper3. That means we need to walk on the edge and consider possibly offensive or unpleasant possibilities if we are going to figure out what is really going on so we can do something to fix things.

  1. I’ve seen any number of scenarios in which the perception that certain topics can’t even be discussed doesn’t erase those ideas from people’s minds. Rather, it pushes them to form groups (the ones that go silent when a woman or minority comes by and we work so hard to eliminate) in which they feel they can comfortably express views they are sympathetic to but are too controversial for general consumption. Unfortunately, when people gather together for the purpose of feeling safe sharing controversial views creates a strong social pressure not to call anyone else’s views in that group out for sexism/racism/etc.. even in a polite friendly way. I’m constantly amazed at how quickly both such groups form and how quickly they descend to the lowest common denominator and serve as a breeding ground where hateful ideas can infect good people because there is no opportunity to apply the corrective of a good counterargument and criticism. 
  2. Taking their complaints at face value would seem to suggest the problem is that suggesting WASP culture (not so named) is superior is racist or at least unacceptable and bad. While those of us immersed in liberal sensibilities naturally flinch a bit when the suggestion is made that one culture is superior to another that doesn’t make the claim wrong or racist. Indeed, we all believe that, at least in the modern context, modern western culture is superior to the violent revenge culture in some New Guinean tribes all things considered (of course cultures have so many traits surely we could cherry pick a few improvements but the original piece doesn’t deny this). Hell, the very idea of tolerance and equality that those on the left are fighting for is a rare value for a culture to have and we are right to identify it as something good and important. But I think this “can’t say one culture is better than another” line isn’t a very charitable interpretation. 
  3. Everyone knows that a great deal of slut-shaming and outfit policing is done to women by women and we’ve learned recently that it is other women who do the majority of interrupting women and may very well be the ones preventing more competitive female involvement. This matches both my experience at caltech (women who had few if any female friends their whole lives were way more likely to just blunder in and shot their load on the conversation or dismiss someone else’s contribution as stupid) and what evolutionary psychology would suggest (men have little interest in policing women but each gender needs to police rivals). Of course, men aren’t on the hook they are just on the hook for something else perpetuating harmful male stereotypes which can harm women as much as they do men (say by men not being willing to become primary caregivers). 

Don’t Change The p-value Threshold

Personally, I think the proposal to ‘change’ the p-value for significant results from .05 to .005 is a mistake. The only sense in which this proposal has any real bite is if journals and hiring committees respond by treating research that doesn’t meet p < .005 as less important but all that does is make the incentives for the kind of behavior causing all the problems much stronger.

I’d much rather have a well designed (ideally pre-registered) trial at p < .05 than a p < .005 result that is cherry picked as a result of after the fact choice of analysis. Rather than making the distinction between well designed appropriate methodology and dangerous potentially misleading methodology more apparent this further obscures it and tells any scientist who was standing on principle they need to stop hoping their better methodology will be appreciated and do something to compete on p-value with papers published using problematic data analysis.

In particular, I think this kind of proposal doesn’t take sufficient account of the economics and incentives of researchers. Yes, p < .005 studies would be more convincing but they also cost more (both in $ and time) so by telling fledgling researchers they need p < .005 you force them to put all their eggs in one basket making dubious data analysis choices that much more tempting when their study fails to meet the threshold.

What we need is more results blind publication processes (in which journals publish the results based merely on a description of the experimental process without knowledge of what the results found). That would both help combat many of these biases and truly evaluate researchers on their ability not their luck. Ideally such studies would be pre-accepted before results were actually analyzed. Of course there still needs to be a place for merely suggestive work that invites further research but it should be regarded as such without any particular importance assigned to p-value.

However, as these are only my brief immediate thoughts I’m quite open to potential counterarguments.

Skepticism About MIT’s Gender Balance Win in MechE

If it really is true, as MIT suggests, that the gender ratio in their department is convincing a substantial percentage of women to enter MechE who otherwise would have avoided a STEM field its a big deal. However, upon reflection there are some aspects that are troubling.

First, as the article suggests, they engage in fairly extensive recruitment and some degree of affirmative action for female students in STEM fields. This calls into question the existence of any such effect as for all we know MIT is just recruiting women interested in MechE away from other schools. Indeed, even just considering the benefit MIT is suggesting (women are more attracted to programs with a reasonable gender balance) one should expect MIT’s efforts here to be worsening the gender balance at other schools like caltech

But if you really believe that gender imbalance both makes life worse for female students and repeals them from the field it seems downright irresponsible to attrach female MechE majors from other schools (without a better understanding of how these effects work). If, as seems quite plausible, the discomfort (and willingness to drop out/not major) is most extreme when the percentage of women is the least (e.g. superlinear as percent goes to 0), then this could be a substantial net harm as the gains from greater gender equality at MIT are more than offset by the decreased gender equality at other schools. It all depends on the specific numbers but its concerning that people seem convinced this is a good thing without even having an intuition about the size and direction of this cross school interaction.

Before anyone applauds these results we really need some good studies checking that MIT’s efforts really are bringing more women into MechE. I hope they are but I fear that they may be doing the exact opposite. If I had to guess I’d bet that any positive effect of gender balance is offset by the fact that MIT is harder/more competitive than the other schools who would otherwise get many of the women MIT recruits and I expect the harder/more competitive a science class the more likely people (of either gender) are to drop out to a less quantitative subject (but that’s just speculation).

Also, I’d like to know what people whether MITs affirmative action efforts create a situation in which men tend to noticeably outperform women. As much as I hated the huge gender ratio at caltech I very much appreciated the fact that they were obviously equals. Now, like everything else, what I appreciated isn’t what matters but it does seem like we should at the very least have a pretty firm grip on what kind of effects on subsequent attitudes affirmative action has before we praise the policy. Even if, this effect doesn’t appear at MIT right now (e.g. they most just steal girls from caltech and cmu) it might if more schools try to implement such a policy.

I find it pretty crazy when MIT is congratulating itself when they don’t seem to have any grip (or at least are hiding it) on what they are trying to achieve or whether their policies achieve it.

Now, of course, most social programs will depend greatly on priors and I’d be happy with a short little explanation about why they think the net benefit of achieving gender balance in their departments is worth the effect it has on other schools. Are they suggesting their policy would and could universalize and benefits would be seen from that? Some words about why would be nice. Also some words about why they have the intuition any blowback is worth the cost. As it is it kinda makes one feel like you are being scammed with a meaningless advertising statistic.

I think its quite possible MIT’s policy is net beneficial but I’ve yet to see any cogent account of why I should think that so if you have one I’d love to hear it.

As an aside I’d add that while I don’t think there is any inherint moral value in making sure men and women are equally represented in every discipline, only in making sure they are equally welcome and have equal access, but I do think there would be substantial societal gains to increasing the number of women in STEM fields. Not only would this make scientists happier (and less socially isolated and less likely to accidentally harass) but merely making it clear that quantitative, systematic thing oriented reasoning isn’t anti-female.

Evaluating Gender Bias Claims In Academia Part 1

Does The Data Support The Interpretation

For a number of reasons I think it’s vital that we have a good empirical grip on the reasons why different genders are over/under represented in various disciplines and at various levels of acclaim in those disciplines. There is the obvious reason, namely that, it is only through such an understanding that we can usefully discuss claims of unfairness and evaluate schemes to address those claims. If we get the reasons for under/over representation in various areas wrong we not only risk failing to correct real instances of unfair based treatment but also undermining the credibility of attempts to address unfair treatment more generally. This isn’t only about avoiding gender based biases but, more broadly, identifying ways in which anyone might face unjust hardship in pursuing their chosen career and succeeding at it1.

Also, even putting questions of fairness and discrimination to the side there are important social and cultural reasons to care about these outcomes. For instance, the imbalance of men and women in STEM fields both imposes personal hardships on both genders in those fields but also creates an excuse for dismissing the style of thinking developed by STEM disciplines. As such, identifying simple changes that could substantially increase female participation in STEM subjects is desirable in and of itself and similar cultural considerations beyond mere fairness extend to other fields. However, I worry that incorrect interpretation of the empirical data could lead us to overlook such changes especially when they don’t fit nicely into the default cultural narrative2.

Point is that I genuinely want to accurately identify the causes of gender differences in educational attainment and academic outcomes. One could be forgiven for thinking that we’ve already nailed down these causes. After all every couple of months one sees a new study being touted in the mainstream media claiming to show sexism playing a role in some educational or professional evaluation. Unfortunately, closer examination of the actual studies conducted often reveals that they don’t actually support the interpretation provided and everyone suffers from a misleading interpretation of the empirical data.

So, in an attempt to get a better picture of what the evidence tells us, every time I see a new study claiming to document gender bias or otherwise explain gender differentials in outcomes I’m going to dive into the results and see if they support the claims made by the article. While I can’t claim that I’m choosing studies to examine in a representative fashion I do hope that comparing the stated claims to what the data supports will help uncover the truth.

Gender and Publishing in Political Science

I ran across this claim that there is gender bias against female authors in political science in the wall street journal blog monkey cage. For once, the mainstream media deserves credit because they accurately conveyed the claims made by the study.

The study claims to show gender bias in political science publication based on an analysis of published papers in political science. By coding the authors of published papers the study gives us the following information about the rate of female publication.

Line A represents the share of women in the ladder faculty at the largest 20 PhD-granting departments in the discipline (27%). Line B represents the share of women among all APSA members (31%). Line C represents the share of women among all newly minted PhDs as reported in the NSF’s survey of earned doctorates.

The paper deserves credit for recognizing that this may reflect some degree of sorting by subfield and recognizing that sorting into subfield might falsely create the impression of bias even when none was present. However, any credit granted should be immediately revoked on account of the following argument.

However, gendered sorting into subfields would not explain is the pattern we observe for the four “generalist” journals in our sample (AJPS, APSR, JOP and POP). These four journals—official journals either of the national association or one of its regional affiliates—are all “generalist” outlets, in that their websites indicate that they are open to submissions across all subfields. Yet, as figure 3 shows, women are underrepresented, against all three benchmarks, in three of those four “generalist” journals.

The mere fact that these are generalist journals in no way means that they are not more likely to publish some kinds of analysis rather than others. As the study goes on to observer women are substantially underrepresented in quantitative and statistical work while overrepresented (at least as compared to their representation at prestigious institutions) in qualitative work. Despite the suggestion by the study authors to the contrary choosing, for valid intellectual (or even invalid gender unrelated) reasons, to value quantitative work more highly and publish it more readily doesn’t constitute gender bias in journal publication in the sense that their conclusions and ethical interpretations assume.

Line A represents the share of women in the ladder faculty at the top 20 PhD-granting departments in the discipline (27%). Line B represents the share of women among all APSA members (31%). Line C represents the share of women among all newly minted PhDs, as reported in the NSF’s survey of earned doctorates (40%).

Ideally, the authors would have provided some more quantitative evaluation of what part of the observed effect was explained by choice of subfield and mode of analysis. However, I think it’s fair to say based on the graph above that women aren’t so overrepresented in publications in qualitative areas for subfield preferences to explain everything so lets put the concern about subfield/analysis type based sorting to one side and return to the primary issue

This paper also deserves praise for recognizing that merely comparing the percentage of women in the field with the percentage of prestigious female publications will merely reflect the fact that past discrimination means the oldest, and most influential, segment of the discipline is disproportionately male. In other words, even assuming that all discrimination and bias magically vanished in the year 2000 one would still expect to find men being published and cited at a greater rate than women for the simple reason that eliminating barriers to female participation biases female representation to the less experienced parts of the discipline. By breaking down authors by their professorial rank the study is able to minimize the extent to which this issue affects their conclusions.

Percentage female authorship by professorial rank

Importantly, in the discussion section (and throughout the paper) the study makes it clear that it takes this result to be evidence of bias. The WSJ post was quite right in understanding the paper to be alleging gender bias in publication. Yes, the study doesn’t claim to decide whether this bias is a result of female authors being rejected more frequently or female authors being less likely to publish in the most prestigious journals but in either case it assumes that the ultimate explanation is pernicious gender bias.

The paper also explores the issue of gender based coauthorship and the relative prevalence of papers with all male authors, mixed gender etc.. etc.. These patterns are used to motivate various speculations about the fears women may face in choosing to coauthor but the complete lack of any attempt to determine to what extent these patterns are simply the result of subfield and analysis type preferences, e.g., quantitative and statistical analysis might lend themselves more frequently to coauthorship, and the relevant percentages of women in those fields undermines any attempt to use this data to support such speculations. While I believe that female scholars do face real concerns about being insufficiently credited as co-authors the ways such concerns could play our are so varied that I don’t think we can use this data to draw the conclusion the study authors do: women aren’t benefiting equally from trends toward coauthorship. However, I’m going to set this issue aside.

Political Science Hiring Biased Toward Women?

At this point one might be inclined to think this paper should get pretty good marks. Sure, I’ve identified a few concerns that aren’t fully addressed but surely it makes a pretty good case for the claim of gender bias in political science? Unfortunately, that’s simply a mirage created by thinking about the data in exactly one way. Notice that one could equally well use the same data and analysis to draw the conclusion: Women Hired in Political Science Despite Fewer Publications. After all the way one gets professorial jobs is by publishing papers and this data suggest that women at the same professional level have less publications than their male colleagues.

Now I think there are multiple plausible ways of resisting the conclusion that this data shows a bias in favor of women in hiring. For one, if past discrimination means that men and women at the same professional level haven’t had the same amount of time to right papers (e.g. women are more likely to have just got the job) then the conclusion is suspect. For another, one might point out that not all the jobs given the same professorial rank in the study are really equivalent. There are further reasons to doubt these conclusions, but each and every reason equally well undermines any support this data provides for claims of gender bias.

Ultimately, I think it’s safe to say that while this study shows that women publish in influential journals at a rate lower than their representation in the political science profession would suggest it does little to identify a cause. If you came into this with the prior that said: the reason women are underrepresented in political science is because they face bias and other obstacles you’ll explain this effect in terms of bias and obstacles. In contrast, if you came in with the prior that said: the reason women are still underrepresented in political science is because of gender related differences in ability/interest (which need not be negative it could as well be a greater affinity for some rival career option) then the data are perfectly compatible with women gravitating towards more qualitative less rigorous aspects of the profession and putting greater focus on teaching and other aspects of the profession that don’t result in publications.

Frankly, I don’t know enough about political science to have much opinion on this point one way or another. However, I do think we can safely mark this study down as misleading at least insofar as it is cited as further evidence of gender bias against women. Don’t get me wrong, I think that is a very plausible interpretation of the data but I’m just sharing the bias I came in with rather than being persuaded by evidence.

  1. For instance, differences in male/female performance might justify studying ways in which standard pedagogy favors/disfavors particular learning styles. Accurate empirical data on this subject, regardless of what it shows about gender, lets us correct the ways in which the current system may be unfair to those with particular learning styles, e.g., consider the recent evidence about how mandated attendance can actually hurt performance by those who don’t find the lecture component of a course useful. 
  2. For instance, I worry that it is precisely women’s better performance in high school mathematics and generally greater willingness to approach subjects as desired by their high school (or early college) teachers rather than going their own way which is responsible for some of the observed disaffinity towards studying higher mathematics among women. Ideally, one would teach mathematics by merely communicating the underlying ideas and allowing students to use their conceptual understanding to solve problems. However, few students have the interest and ability to, say, use their conceptual understanding of the derivative to find the maximum value of a given function and the educational system is unwilling to abandon the idea that almost all college freshmen should be able to solve such problems. As a result lower level mathematics is forced to adopt a formulaic approach the favors rote memorization of algorithms meaning that gaining real insight and experiencing mathematics as an enjoyable puzzle often requires rejecting the approach seen in the classroom and working things out on one’s own. I worry that we lose many women who might otherwise be interested in mathematics simply because they are more devoted to working within the framework they are given but because this is largely seen as a positive value it gets neglected as a potential problem. If true, it might be that simple interventions like explicitly encouraging students to deviate from the rote rules being taught if they understand enough to do so could make a big difference.