Benefits To Bullying

When it comes to assessing hypotheses of evolutionary function, there is a troublesome pair of intuitions which frequently trip many people up. The first of these is commonly called the naturalistic fallacy, though it also goes by the name of an appeal to nature: the idea that because something is natural, it ought to be good. As a typical argument using this line might go, because having sex is natural, we ought to – morally and socially – approve of it. The corresponding intuition to this is known as the moralistic fallacy: if something is wrong, then it’s not natural (or, alternatively, if something is good, it is natural). An argument using this type of reasoning might (and has, more or less) gone, because rape is morally wrong, it cannot be a natural behavior. In both cases, ‘natural’ is a bit of a wiggle word but, in general, it seems to refer to whether or not a species possesses some biological tendency to engage in the behavior in question. Put another way, ‘natural’ refers to whether a species possesses an adaptation(s) that functions so as to bring about a particular outcome. Extending these examples a little further, we might come up with the arguments that, because humans possess cognitive mechanisms which motivate sexual behavior, sex must be a moral good; however, because rape is a moral wrong, the human must not contain any adaptations that were selected for because they promoted such behavior.

An argument with which many people appear to disagree, apparently

This type of thinking is, of course, fallacious, as per the namesakes of the two fallacies. It’s quite easy to think of many moral wrong which might increase one’s reproductive fitness (and thus select for adaptations that produce them), just as it is easy to think of morally-virtuous behaviors that could lower one’s fitness: infanticide is certainly among the things people would consider morally wrong, and yet there is often an adaptive logic to be found in the behavior; conversely, while the ideal of universal altruism is praised by many as morally virtuous, altruistic behavior is often limited to contexts in which it will later be reciprocated or channeled towards close kin. As such, it’s probably for the best to avoid tethering one’s system of moral approval to natural-ness, or vice versa; you end up in some weird places philosophically if you do. Now this type of thinking is not limited to any particular group of people: scientists and laypeople alike can make use of these naturalistic and moralistic intuitions (intentionally or not), leading to cases where hypotheses of function are violently rejected for even considering that certain condemned behaviors might be the result of an adaptation for generating them, or other cases where weak adaptive arguments are made in the service of making other behaviors with which the arguer approves seem more natural and, accordingly, more morally acceptable.

With that in mind, we can turn to the matter of bullying: aggression enacted by more powerful individuals against weaker ones, typically peaking in frequency during adolescence. Bullying is a candidate behavior that might fall prey to the former fallacies because, well, it tends to generate many consequences people find unpleasant: having their lunch money taken, being hit, being verbally mocked, having slanderous rumors about them being spread, or other such nastiness. As bullying generates such proximately negative consequences for its victims, I suspect that many people would balk at the prospect that bullying might reflect a class of natural, adaptive behaviors, resulting in the bully gaining greater access to resources and reputation; in other words, doing evolutionarily useful things. Now that’s not to say that if you were to start bullying people you would suddenly find your lot in life improving, largely because bullying others tends to carry consequences; many people will not sit idly by and suffer the costs of your bullying; they will defend themselves. In order for bullying to be effective, then, the bully needs to possess certain traits that minimize, withstand, or remove the consequences of this retaliation, such as a greater physical formidability than their victim, a stronger social circle willing to protect them, or other means of backing up their aggression.

Accordingly, only those in certain conditions and possessing particular traits are capable of effectively bullying others (inflicting costs without suffering them in turn). Provided that is the case, those who engaged in bullying behaviors more often might be expected to achieve correspondingly greater reproductive success, as the same traits that make bullying an effective strategy also make the bully an attractive mating prospect. It’s probably worse to select a mate unable to defend themselves from aggression, relative to one able and willing to do so; not only would your mate (and perhaps you) be exploited more regularly, but such traits may well be passed onto your children in turn, leaving them open for exploitation as well. Conversely, the bully able to exploit others can likely can access to more plentiful resources, protect you from exploitation, and pass such useful traits along to their children. That bullying might have an adaptive basis was the hypothesis examined in a recent paper by Volk et al (2015). As noted in their introduction, previous data on the subject is consistent with the possibility that bullies are actually in relatively better condition than their victims, with bullies displaying comparable or better mental and physical health, as well as improved social and leadership skills, setting the stage for the prospect of greater mating success (as all of those traits are valuable in the mating arena). Findings like those run counter to some others suggestions floating around the wider culture that people bully others precisely because they lack social skills, intelligence, or are unhappy with themselves. While I understand that no one is particularly keen to paint a flattering picture of people they don’t like and their motives for engaging in behavior they seek to condemn, it’s important to not lose sight of reality while you try reduce the behavior and condemn its perpetrators.

“Sure, he does hit me regularly, but he’s a really great guy otherwise”

Volk et al (2015) examined the mating success of bullies by correlating people’s self-reports of their bullying behavior with their reports of dating and sexual behavior across two samples: 334 younger adolescents (11-18 years old) and 143 college freshman, all drawn from Canada. Both groups answered questions concerning how often they engaged in, and were a victim of, bullying behaviors, whether they have had sex and, if they had, how many partners they’ve had, whether they have dated and, if so, how many people they’ve dated, as well as how likable and attractive they found themselves to be. Self-reports are obviously not the ideal measures of such things, but at times they can be the best available option.

Focusing on the bullying results, Volk et al (2015) reported a positive relationship between bullying and engaging in dating and sexual relationships in both samples: controlling for age, sex, reported victimization, attractiveness, and likability, bullying not only emerged a positive predictor as to whether the adolescent had dated or had sex at all (about 1.3 to 2 times more likely), but also correlated with the number of sexual and, sometimes, dating partners; those who bullied people more frequently tended to have a greater number of sexual partners, though this effect was modest (bs ranging from 0.2 to 0.26). By contrast, being a victim of bullying did not consistently or appreciably effect the number of sexual partners one had (while victimization was positively correlated with participant’s number of dating partners, it was not correlated with their number of sexual partners. This might reflecting the possibility that those who seek to date frequently might be viewed as competitors by other same-sex individuals and bullied in order to prevent such behavior from taking place, though that much is only speculation).

While this data is by no means conclusive, it does present the possibility that bullying is not indicative of someone who is poor shape physically, mentally, or socially; quite the opposite, in fact. Indeed, that is probably why bullying often appears to be so one-sided: those being victimized are not doing more to fight back because they are aware of how well that would turn out for them. Understanding this relationship between bullying and sexual success might prove rather important for anyone looking to reduce the prevalence of bullying. After all, if bullying is providing access to desirable social resources – including sexual partners – it will be hard to shift the cost/benefit analysis away from bullying being the more attractive option barring some introduction of more attractive alternatives for achieving that goal. If, for instance, bullying serves a cue that potential mates might use for assessing underlying characteristics that make the bully more attractive to others, finding new, less harmful ways of signaling those traits (and getting bullies to use those instead) could represent a viable anti-bully technique.

But, until then, this kid is going to get so laid

As these relationships are merely correlational, however, there are other ways of interpreting them. It could be possible, for example, that the relationship between bullying and sexual success is accounted for by those who bully being more coercive towards their sexual partners as well as their victims, achieving a greater number of sexual partners, but not in the healthiest fashion. This interpretation would be somewhat complicated by the lack of a sex differences between men and women in the current data, however, as it seems unlikely that women who bully are also more likely to coerce their male partners into sex they don’t really want. The only sex difference reported involved the relationship between bullying and dating, with the older sample of women who bullied people more often having a greater number of dating relationships (r = 0.5), relative to men (r = 0.13), as well as a difference in the younger sample with respect to desire for dating relationships (female r = 0.28, male r = 0.03). It is possible, then, that men and women might bully others, at least at times, to obtain different goals, which ought to be expected when the interests of each sex diverge. Understanding those adaptive goals should prove key for effectively reducing bullying; at least I feel that understanding would be more profitable than positing that bullies are mean because they wish to make others as miserable as they are, crave attention, or other such implausible evolutionary functions.

References: Volk, A., Dane, A., Marini, Z., & Vaillancourt, T., (2015). Adolescent bullying, dating, and mating: Testing an evolutionary hypothesis. Evolutionary Psychology, DOI: 10.1177/1474704915613909

Inequality Aversion, Evolution, And Reproduction

Here’s a scenario that’s not too difficult to imagine: a drug company has recently released a paper claiming that a product they produce is both safe and effective. It would be foolish of any company with such a product to release a report saying their drugs were in any way harmful or defective, as it would likely lead to a reduction in sales and, potentially, a banning or withdrawal of the drugs from the wider market. Now, one day, an outside researcher claims to have some data suggesting that drug company’s interpretation of their data isn’t quite right; once a few other data points are considered, it becomes clear that the drug is only contextually effective and, in other cases, not really effective at all. Naturally, were some representatives of the drug company asked about the quality of this new data, one might expect them to engage in a bit of motivated reasoning: some concerns might be raised about the quality of the new research that otherwise would not be, were its conclusions different. In fact, the drug company would likely wish to see the new research written up to be more supportive of their initial conclusion that the drug works. Because of their conflict of interests, however, expecting an unbiased appraisal of the research suggesting the drug is actually much less effective than previously stated from those representatives would be unrealistic. For this reason, you probably shouldn’t ask representatives from the drug company to serve as reviewers for the new research, as they’d be assessing both the quality of their own work and the quality of the work of others with factors like ‘money’ and ‘prestige’ on the table.

“It must work, as it’s been successfully making us money; a lot of money”

On an entirely unrelated note, I was the lucky recipient of a few comments about some work of mine concerning inequality aversion: the idea that people dislike inequality per se (or at least when they get the short end of the inequality stick) and are willing to actually punish it. Specifically, I happen to have some data that suggests people do not punish inequality per se: they are much more interested in punishing losses, with inequality only playing a secondary role in – occasionally – increasing the frequency of that punishment. To place this in an easy example, let’s consider TVs. If someone broke into your house and destroyed your TV, you would likely want to see the perpetrator punished, regardless of whether they were richer or poorer than you. Similarly, if someone went out and bought themselves a TV (without having any effect on yours), you wouldn’t really have any urge to punish them at all, whether they were poorer or richer than you. If, however, someone broke into your house and took your TV for themselves, you would likely want to see them punished for their actions. However, if they were actually poorer than you, this might incline you to go after the thief a bit less. This example isn’t perfect, but it basically describes what I found.

Inequality aversion would posit that people show a different pattern of punitive sentiments: that you would want to punish people who end up better off than you, regardless of how they got that way. This means that you’d want to punish the guy who bought the TV for himself if it meant he ended up better off than you, even though he had no effect on your well-being. Alternatively, you wouldn’t be particularly inclined to punish the person who stole/broke your TV either unless they subsequently ended up better off than you. If they were poorer than you to begin with and were still poorer than you after stealing/destroying the TV, you ought not to be particularly interested in seeing them punished.

In case that wasn’t clear, the argument being put forth is that how well you are doing, relative to others ought to be used as an input for punishment decisions to a greater extent – a far greater one – than absolute losses or gains are.

Now there’s a lot to say about that argument. The first thing to say is that, empirically, it is not supported by the data I just mentioned: if people were interested in punishing inequality itself, they ought to be willing to punish that inequality regardless of how it came about: stealing a TV, buying a TV, or breaking a TV should be expected to prompt very similar punishment responses; it’s just that they don’t: punishment is almost entirely absent when people create inequality by benefiting themselves at no cost to others. By contrast, punishment is rather common when costs are inflicted on someone, whether those costs involve taking (where one party benefits while the other suffers) or destruction (where one party suffers a loss at no benefit to anyone else). On those grounds alone we can conclude that something is off about the inequality aversion argument: the theory does not match the data. Thankfully – for me, anyway – there are also many good theoretical justifications for rejecting inequality aversion.

“It’s a great home in a good neighborhood; pay no mind to the foundation”

The next thing to say about the inequality argument is that, in one regard, it is true: relative reproduction rates determine how quickly the genes underlying an adaptation spread – or fail to spread – throughout the population. As resources are not unlimited, a gene that reproduces itself 1.1 times for each time an alternative variant reproduces itself once will eventually replace the other in the population entirely, assuming that the reproductive rates stay constant. It’s not enough for genes to reproduce themselves, then, but for them to reproduce themselves more frequently than competitors if they metaphorically hope to stick around in the population over time. That this much is true might lure people into accepting the rest of the line of reasoning, though to do so would be a mistake for a few reasons.

Notable among this reasons is that “relative reproductive advantage” does not have three modes of “equal”, “better”, or “worse”. Instead, relative advantage is a matter of degree: a gene that reproduces itself twice as frequently as other variants is doing better than a gene that does so with 1.5 times the frequency; a gene that reproduces itself three times as frequently will do better still, and so on. As relative reproductive advantages can be large or small, we ought to expect mechanisms that generate larger relative reproductive advantages to be favored over those which generate smaller ones. On that point, it’s worth bearing in bearing in mind that the degree of relative reproductive advantage is an abstract quantity compromised of absolute differences between variants. This is the same point as noting that, even if the average woman in the US has 2.2 children, no woman actually has two-tenths of a child laying around; they only come in whole numbers. That means, of course, that evolution (metaphorically) must care about absolute advantages to precisely the same degree it cares about relative ones, as maximizing a relative reproductive rate is the same thing as maximizing an absolute reproductive rate.

The question remains, however, as to what kind of cognitive adaptations would arise from that state of affairs. On the one hand, we might expect adaptations that primarily monitor one’s own state of affairs and makes decisions based on those calculations. For instance, if a male with two mates has an option to pursue a third and the expected fitness benefits of doing so outweigh the expected costs, then the male in question would likely pursue the opportunity. On the other hand, we might follow the inequality aversion line of thought and say that the primary driver of the decision to pursue this additional mate should be how well the male in question is doing, relative to his competitors. If most (or should it be all?) of his competitors currently have fewer than two mates, then the cognitive mechanisms underlying his decision should generate a “don’t pursue” output, even if the expected fitness costs are smaller than the benefits. It’s hard to imagine how this latter strategy is expected to do better (much less far better) than the former, especially in light of the fact that calculating how everyone else is doing is more costly and prone to errors than calculating how you are doing. It’s similarly hard to imagine how the latter strategy would do better if the state of the world changes: after all, just because someone is not currently doing as well as you, it does not mean they won’t eventually be. If you miss an opportunity to be doing better today, you may end up being relatively disadvantaged in the long run.

“I do see her more than the guy she’s cheating on me with, so I’ll let it slide…”

I’m having a hard time seeing how a mechanism that operates on an expected fitness cost/benefit analysis would get out-competed by a more cognitively-demanding strategy that either ignores such a cost/benefit strategy or takes it and adds something irrelevant into the calculations (e.g.,” get that extra benefit, but only so long as other people are currently doing better than you)”. As I mentioned initially, the data shows the absolute cost/benefit pattern predominates: people do not punish others primarily on the basis of whether they’re doing better than them or not; they primarily punish on the basis of whether they experienced losses. Nevertheless inequality does play a secondary role – sometimes – in the decision regarding whether to punish someone for taking from you. I happen to think I have an explanation as to why that’s the case but, as I’ve also been informed by another helpful comment (which might or might not be related to the first one), speculating about such things is a bit on the taboo side and should be avoided. Unless one is speculating that inequality, and not losses, primarily drives punishment, that is.

Sexism: One More Time With Feeling

For whatever reason, a lot of sexism-related pieces have been crossing my desk lately. It’s not that I particularly mind; writing about these papers is quite engaging, and many people – no matter the side of the issue they tend to find themselves falling on – seem to share a similar perspective when it comes to reading about them (known more colloquially as the Howard Stern Effect). Now, as I’ve said before on several of the occasions I’ve written about them, the interpretations of the research on sexism – or sometimes the research itself – feels rather weak. The main reason I’ve found this research to feel so wanting centers around the rather transparent and socially-relevant persuasive messages that reside in such papers: when people have some vested interest in the outcome of the research – perhaps because it might lend legitimacy to their causes or because it paints a socially-flattering picture of their group – this opens the door for research designs and interpretations of data that can get rather selective. Basically, I have a difficult time trusting that truth will fall out of sexism research for the same reason I wouldn’t take a drug company’s report about the safety of their product at face value; there’s just too much on the line socially to not be skeptical.

“50% of the time it worked 100% of the time. Most of the rats didn’t even die!”

Up for consideration today is a paper examining how men and women perceive the quality of sexism research, contingent on the results of it (Handley et al, 2015). Before getting into the meat of this paper, I want to quote a passage from its introduction to applaud the brilliant tactical move the authors make (and to give you a sense for why I experience a certain degree of distrust concerning sexism research). When discussing how some of the previous research published by one of the authors was greeted with skepticism by predominately men – at least according to an informal analysis of online comments replying to coverage of it – the authors have this to say:

“…men might find the results reported by Moss-Racusin et al. threatening, because remedying the gender bias in STEM fields could translate into favoring women over men, especially if one takes a zero-sum-gain perspective. Therefore, relative to women, men may devalue such evidence in an unintentional implicit effort to retain their status as the majority group in STEM fields.”

This is just a fantastic passage for a few reasons. First, it subtlety affirms the truth of the previous research; after all, if there did not exist a real gender bias, there would be nothing in need of being remedied, so the finding must therefore reflect reality. Second. the passage provides a natural defense against future criticism of their work: anyone who questions the soundness of their research, or their interpretation of the results, is probably just biased against seeing the plainly-obvious truth they have stumbled upon because they’re male and trying to maintain their status in the world. For context, it’s worth noting that I have touched upon the piece in question before, writing, “Off the top of my head, I see nothing glaringly wrong with this study, so I’m fine with accepting the results…“. While I think the study in question seemed fine, I nevertheless questioned how well their results mesh with other findings (I happen to think there are some inconsistencies that would require a rather strange kind of discrimination be at play in the real world) and I was not overly taken with their interpretation of what they found.

With that context in mind, the three studies in the paper followed the same general method: an abstract of some research was provided to men and women (the first two studies used the abstract from one of the authors; the third used a different one). The subjects were asked to evaluate, on a 1-6 scale, whether they agreed with the author’s interpretation of the results, whether the research was important, whether the abstract was well written, and what their overall evaluation of the research was. These scores were then averaged into a single measure for each subject. In the third experiment the abstract itself was modified to either suggest that a bias favoring men and disfavoring women in STEM fields was uncovered by the research, or that no bias was found (why no condition existed in which the bias favored women I can’t say, but I think it would have been a nice addition to the paper). Just as with the previous paper, I see nothing glaringly wrong with their methods (beyond that omission), so let’s consider the results.

The first sample was comprised of 205 Mturk participants, and found that men were somewhat less favorable about the research that found evidence of sexism in STEM fields (M = 4.25) relative to women (M = 4.66). The second sample was made up of 205 academics from an unnamed research university and the same pattern was observed: overall, male faculty assessed the research somewhat less favorably (M = 4.21) than female faculty (M = 4.65). However, an important interaction emerged: the difference in this second sample was due to male-female differences within STEM fields. Male STEM faculty were substantially less positive about the study (M = 4.02) than their female counterparts (M = 4.80); non-STEM faculty did not differ in this respect, both falling right in between those two points (Ms = 4.55). Now it is worth mentioning that the difference between the STEM and non-STEM male faculty was statistically significant, but the difference between the female STEM and non-STEM faculty was not. Handley et al (2015) infer from that result that, “…men in STEM displayed harsher judgments of Moss-Racusin et al.’s research, not that women in STEM exhibited more positive evaluations of it“. This is where I’m going to be sexist and disagree with the author’s interpretation, as I feel it’s also worth noting that the sample size of male STEM faculty (n = 66) was almost twice as large as the female sample (n = 38), which likely contributed to that asymmetry in statistical significance. Descriptively speaking, STEM men were less accepting of the research and STEM women were more accepting of it, relative to the academics for whom this finding would be less immediately relevant.

“The interpretation of this research determines who deserves a raise, so please be honest.”

The third experiment that modified the abstract to contain a finding of either sexism against women or no sexism also used an Mturk sample of 303 people, rather than faculty. The same basic pattern was found here: when the research reported a bias against women, men were less favorable towards it (M = 3.65) than if it found no bias (M = 3.83); women showed the opposite pattern (Ms =  3.86 and 3.59, respectively). So – taken together – there’s some neat evidence here that the relevance of a research finding affects how that finding is perceived. Those who have something to gain by the research finding sexism (women, particularly those in STEM) tended to be slightly more favorable towards research that found it, whereas those who had something to lose (men, particularly those in STEM) tended to be slightly unfavorable towards research finding sexism. This isn’t exactly new – research on the idea has dated back at least two decades - but it fits well with what we know about how motivated reasoning works.

I want to give credit where credit is due: Handley et al (2015) do write that they cannot conclude that one gender is more biased than the other; just that gender appears to – sometimes – bias how sexism research is perceived to some degree. Now that tentative conclusion would be all well and good were it a consistent theme throughout their paper. However, the examples raised in the write-up universally center around how men might find findings of sexism threatening and how women are known to be disadvantaged by it; not on how women might be strategically inclined towards such research because it suits their goals (as, to remedy anti-female bias, female-benefiting plans may well have to be enacted). Even a quick reading of the paper should demonstrate that the authors are clearly of the view that sexism is a rather large problem for STEM fields, writing about how female participation needs to be increased and encouraged. That would seem to imply that anyone who denies the importance of the research reporting sexism is the one with the problematic bias, and that is a much less tentative way to think about the results. In the spirit of furthering their own interests, the authors further note how these biases could be a real problem for people publishing sexism research, as many of the people reviewing research articles are likely to be men and, accordingly, not necessarily inclined towards it (which, they note, makes it harder for them to publish in good journals and get tenure).

Handley et al’s (2015) review of the literature also comes off as rather one-sided, never explicitly discussing other findings that run counter to the idea that women experienced a constant stream of sexist discrimination in academia (like this finding: qualified women are almost universally preferred to qualified men by hiring committees, often by a large margin). Funnily enough, the authors transition from writing about how the evidence of sexism against women in STEM is “mounting” in the introduction to how the evidence is “copious” by the discussion. This one-sided treatment can be seen again around the very end of their discussion (in the “limitations and future directions” section) when Handley et al (2015) note that they failed to find an effect they were looking for: abstracts that were ostensibly written by women were not rated any differently than abstracts presented as being written by men (they hoped to find the female abstracts to be rated as lower quality). For whatever reason, however, they neglected to report this failure in their results section, where it belonged; indeed, they failed to mention that this was a prediction they were making the main paper at all, even though it was clearly something they were looking to find (else why would they include that factor and analyze the data in the first place?). Not mentioning a prediction that didn’t work out upfront strikes me as somewhat less than honest.

“Yeah; I probably should have mentioned I was drunk before right now. Oops”

Taking these results at face value, we can say that people who are motivated to interpret results in a particular way are going to be less than objective about that work, relative to someone with less to gain or lose. With that in mind, I would be inherently skeptical of the way sexist biases are presented in the literature more broadly and how they’re discussed in the current paper: the authors clearly have a vested interest in their research uncovering particular patterns of sexism, and in their interpretations of their data being accepted by the general and academic populations. That doesn’t make them unique (you could describe almost all academic researchers that way), nor does it make their results incorrect, but it does seem to make their presentation of these impactful issues seem painfully one-sided. This is especially concerning because these are matters which many feel carry important social implications. Bear in mind, I am not taking issue with the methods or the data presented in the current paper; those seem fine; what I take issue with is the interpretation and presentation of them. Then again, perhaps these only seem like issues to me because I’m a male STEM major…

References: Handley, I., Brown, E., Moss-Racusin, C., & Smith, J. (2015). Quality of evidence revealing subtle gender biases in science is in the eye of the beholder. Proceedings of the National Academy of Science, 112, 13201-13206.

The Very Strange World Of Sexism Research

Just from reading that title, many of you are likely already experiencing a host of emotions concerning the topic of sexism. It’s one of those topics that lights more than the usual number of metaphorical fires under people’s metaphorical asses, as well it should: it’s one of the labels tethered to people’s value as associates in the social world. Being branded a sexist is bad for business, socially, professionally, and otherwise. Conversely, being able to label others as sexist can be helpful for achieving your social goals (as others might acquiesce to your demands to avoid the label), whereas being thought of as someone who throws around the label inappropriately can lead to condemnation of its own. Because there is so much on the line socially when it comes to sexism, the topic tends to be one that migrates away from the realm of truth to the realm of persuasion; a place where truth might or might not be present, but is besides the point anyway. It also yields some truly strange papers with some even stranger claims.

“I’d like to introduce you to my co-authors…”

Some of these strange claims – such as the Ambivalent Sexism Inventory’s (ASI) interpretations of sexism – I’ve written about before. Specifically, I found it to be a rather odd scale for assessing sexism; perhaps being more suited for assessing whether someone is likely to identify as a feminist (which, to head off any comments to the contrary, is not the same thing). For instance, one question on the ASI concerns whether “most women interpret innocent remarks or acts as being sexist”, which is a nice way of building into your scale a way of denigrating people who think the scale misinterprets certain remarks or acts as indicating sexism. While it’s open to interpretation whether the scale measures what it claims to measure, it’s also an open question as to how well the answers to the inventory relate to actual sexist behaviors. Luckily, the study I wanted to discuss today sought to examine just that very thing, which is a happy little coincidence. Unfortunately, just as the interpretation of sexist attitudes is open to interpretation, the paper’s interpretation of sexist behavior is also rather open to interpretation, as I will soon discuss. Also unfortunately, the study sought to develop an implicit association task (IAT) to measure these sexism scores as well, and my thoughts on IATs have historically been less than positive.

The paper in question (de Oliveira Laux, Ksenofontov, & Becker, 2015) begins with a discussion of two types of sexism (against women) assessed by the ASI: benevolent and hostile sexism. The former refers to attitudes which hold women in high regard and to the prospect that men ought to behave altruistically towards them; the latter type of sexism refers largely to attitudes concerning whether women seek social advantages by overstating complaints and making unreasonable demands. At least that’s my interpretation of what the inventory is measuring when looking at the questions it asks; if you asked the authors of the current paper, they would tell you that hostile sexism inventory is measuring “antipathy towards non-traditional women who are perceived as challenging male power and as posing a threat for men” and that benevolent sexism measures “subjectively positive but patronizing view of women who conform to traditional roles“. These definitions will be important later, so keep them in mind.

In either case, the researchers wondered whether people’s explicit responses to these questions might be hiding their true levels of sexism, as hostile sexism is socially condemned. Accordingly, their first goal was to try and create an IAT that measured implicit hostile and benevolent sexism. They sought to develop this implicit measure despite their (surely a priori) expectation that it would be less predictive of sexist behavior than the explicit measures, which is one of those stranger aspects of this research I mentioned before: they were seeking to create an implicit measure that does worse at predicting behavior than existing, explicit ones. Undeterred by that expectation, the researchers recruited 126 males to take their sexism IATs and fill out the ASI. The benevolent sexism IAT portion had participants view 10 comics in which the man or woman was taking the active role. More precisely, a man/woman was either: (1) protecting the other with a gun, (2) proposing, (3) carrying their spouse through a door, post-marriage, (4) protecting the other with what looks like a stick, and (5) putting a coat on the other. The hostile sexism portion had words – not pictures – referring to “traditional” women (housewife/mother) or “non-traditional” women (feminist/women’s rights activists). Participants were supposed to sort these pictures/words into pleasant and unpleasant categories, I think; the section concerning the methods is less than specific about what the instructions behind the task were.

“Precise reporting is a tool of patriarchy”

Now the study already has a problem here in that it’s unclear what precisely participants are responding too when they see the pictures in the benevolent IAT: might they find the active women or the man cowering behind her the unpleasant part of the picture they’re categorizing? That concern aside, there were indeed correlations between the IATs and their explicit counterpart measures on the ASI: those who were higher in benevolent sexism were quicker to pair women in the protector role with negative words, and those higher in hostile sexism were quicker to pair feminism with negative words. Sure; both of these correlations were about r = .2, but they were not statistically zero. Further, the IAT measures of benevolent and hostile sexism did not correlate with each other (r = -.12), even though the explicit measures on the ASI did (r = .54). Naturally, the authors interpreted this as providing “strong support” for the validity of these IAT measures.

As a quick aside, I find this method a bit peculiar. The authors believe that hostile sexism might be consciously suppressed, meaning that the explicit measures of it might not be particularly good at measuring people’s actual attitudes. However, they’re trying to validate their implicit measures by correlating them with the explicit ones which they just suggested might not be accurate reflections of attitudes. That makes things rather difficult to interpret if you want to know which measure – explicit or implicit – taps into the construct better. Moving on…

In the second phase of the study, 83 of the original participants were brought back to assess their sexist behavior. What kind of behaviors were being assessed as sexist? Funny I should assumed you asked: in the benevolent sexism condition, participants were paired with a female confederate and asked to do a bit of role playing across three scenarios. During these role playing scenarios, the participants could choose between a pre-selected “sexist” action (like paying for the meal on their anniversary, expressing concern over their sister’s safety were she to take an internship counseling rapists, or asking that their female partner to create a shopping list for baking a cake while he allocated himself the job of creating a shopping list for heavy tools) or non-sexist ones (like simply expressing a concern that his sister would be disappointed by the rapist-counseling internship; not that she might be endangered by it, as that would be sexist).

Assessing the hostile sexist behaviors involving pairing the men with other male confederates. The job of this male-male pair was to review and recommend jokes. Each were given 9 cards that contained either a sexist joke and a neutral one, or two neutral ones.  They were asked to take turns choosing which joke they liked more and indicated whether they would recommend it to others. If both agreed it should be recommended to others, it would be passed on to the next group completing the task. Here’s an example of a neutral joke:

“Who invented the Triathlon? – The Polish. They walk to the swimming pool, swim one round and return home on a bike.”

If you can make sense of it, please let me know in the comments, because I certainly can’t parse what’s supposed to be funny about it, or even what it’s supposed to mean. We can also consider the example of a joke tapping hostile sexism:

“Why does a woman have one brain cell more than a horse? So that she doesn’t drink from the bucket while washing the stairs.”

While that joke does indeed sounds mean, I have some reservations as to whether it counts as hostile sexism the way the authors define it: as an antipathy towards non-tradition women who challenge male power structures. In that joke, the woman is not engaged in a non-traditional task, nor is she challenging male power, as far as I can tell. While the joke might correspond to what people think when they hear the words “hostile sexism” – i.e., being mean to women because of their sex –  it does not correspond well to the definition the authors use. It seems there are better examples of jokes that reflect the hostile sexism the authors hope to tap into (though these jokes no doubt tap many other things as well).

Like this one, for instance.

Skipping over one other role-playing task for length constraints, the final part of the hostile sexist behavior assessment examined one last sexist behavior: whether the participant would sign a petition for a men’s rights organization that the male confederate showed him. Signing the petition was counted as a sexist behavior, while not signing was counted as non-sexist. Take from that what you will.

As for the results of this second portion, the participant’s behavioral sexism scores did not correlate with their IAT measures of benevolent sexism at all, whether that behavior was supposed to count as benevolent or hostile. The IAT measure of hostile sexism did, for whatever reason, correlate with both benevolent and hostile behaviors, but correlated more strongly with benevolent sexism (rs = .33 and .21, respectively), which, as far as I can tell, was not predicted. Perhaps the evidence in favor the validity of these IAT measures was not quite as strong as the authors had claimed earlier. Also, as apparently expected, the implicit measures correlated less well with behavior than the explicit measures in all cases anyway (the correlations between explicit answers and behavior were both about .6), making one wonder why they were developed.

Interpreting these results generously, we might conclude that explicit attitudes predict behaviors –  a finding that many would not consider particularly unique – and that implicit associations predict behaviors less well or not at all. Interpreting these results less charitably, we might conclude that we don’t really learn much about sexism or attitudes, but learn instead that the authors likely identify as feminists and, perhaps, feel that those who disagree with them ought to be labeled as sexists, as they’re willing to stretch the definition of sexism far beyond its normal meaning while only studying the behavior of men. If you lean towards that second interpretation, however, it probably means you’re sexist.

References: de Oliveira Laux, S., Ksenofontov, I., & Becker, J. (2015). Explicit but not implicit sexist beliefs predict benevolent and hostile sexist behavior. European Journal of Social Psychology, 45, 702-715.