Chivalry Isn’t Dead, But Men Are

In the somewhat-recent past, there was a vote in the Senate held on the matter of whether women in the US should be required to sign up for the selective service – the military draft – when they turn 18. Already accepted, of course, was the idea that men should be required to sign up; what appears to be a relatively less controversial idea. This represents yet another erosion of male privilege in modern society; in this case, the privilege of being expected to fight and die in armed combat, should the need arise. Now whether any conscription is likely to happen in the foreseeable future (hopefully not) is a somewhat different matter than whether women would be among the first drafted if that happened (probably not), but the question remains as to how to explain this state of affairs. The issue, it seems, is not simply one of whether men or women are better able to shoulder the physical demands of combat, however; it extends beyond military service into intuitions about real and hypothetical harm befalling men and women in everyday life. When it comes to harm, people seem to generally care less about it happening to men.


One anecdotal example of these intuitions I’ve encountered during my own writing is when an editor at Psychology Today removed an image in one my posts of a woman undergoing bodyguard training in China by having a bottle smashed over her head (which can be seen here; it’s by no means graphic). There was a concern expressed that the image was in some way inappropriate, despite my posting of other pictures of men being assaulted or otherwise harmed. As a research-minded individual, however, I want to go beyond simple anecdotes from my own life that confirm my intuitions into the empirical world where other people publish results that confirm my intuitions. While I’ve already written about this issue a number of times, it never hurts to pile on a little more.  Recently, I came upon a paper by FeldmanHall et al (2016) that examined these intuitions about harm directed towards men and women across a number of studies that can help me do just that.

The first of the studies in the paper was a straightforward task: fifty participants were recruited from Mturk to respond to a classic morality problem called the footbridge dilemma. Here, the life of five people can be saved from a train by pushing one person in front of it. When these participants were asked whether they would push a man or woman to their death (assuming, I think, that they were going to push one of them), 88% of participants opted for killing the man. Their second study expanded a bit on that finding using the same dilemma, but asking instead how willing they would be (on a 1-10 scale) to push either a man, woman, or a person of unspecified gender without other options existing. The findings here with regard to gender were a bit less dramatic and clear-cut: participants were slightly more likely to indicate that they would push a man (M = 3.3) than a woman (M = 3.0), though female participants were nominally less likely to push a woman (roughly M = 2.3) than men were (roughly M = 3.8), perhaps counter to what might be predicted. That said, the sample size for this second study was fairly small (only about 25 per group), so that difference might not be worth making much over until more data is collected.

When faced with a direct and unavoidable trade-off between the welfare of men and women, then, the results overwhelmingly showed that the women were being favored; however, when it came to cases where men or women could be harmed alone, there didn’t seem to be a marked difference between the two. That said, that moral dilemma alone can only take us so far in understanding people’s interests about the welfare of others in no small part because of their life-and-death nature potentially introducing ceiling effects (man or woman, very few people are willing to throw someone else in front of a train). In other instances where the degree of harm is lowered – such as, say, male vs female genital cutting – differences might begin to emerge. Thankfully, FeldmanHall et al (2016) included an additional experiment that brought these intuitions out of the hypothetical and into reality while lowering the degree of harm. You can’t kill people to conduct psychological research, after all.


In the next experiment, 57 participants were recruited and given £20. At the end of the experiment, any money they had would be multiplied by ten, meaning participants could leave with a total of £200 (which is awfully generous as far as these things go). As with most psychology research, however, there was a catch: the participants would be taking part in 20 trials where £1 was at stake. A target individual – either a man or a woman – would be receiving a painful electric shock, and the participants could give up some of that £1 to reduce its intensity, with the full £1 removing the shock entirely. To make the task a little less abstract, the participants were also forced to view videos of the target receiving the shocks (which, I think, were prerecorded videos of real shocks – rather than shocks in real time – but I’m not sure from my reading of the paper if that’s a completely accurate description).

In this study, another large difference emerged: as expected, participants interacting with female targets ended up keeping less money by the end (M = £8.76) than those interacting with male targets (M = £12.54; d = .82). In other words, the main finding of interest was that participants were willing to give up substantially more money to prevent women from receiving painful shocks than they were to help men. Interestingly, this was the case in spite of the facts that (a) the male target in the videos was rated more positively overall than the female target, and (b) in a follow-up study where participants provided emotional reactions to thinking about being a participant in the former study, the amount of reported aversion to letting the target suffer shocks was similar regardless of the target’s gender. As the authors conclude:

While it is equally emotionally aversive to hurt any individual—regardless of their gender—that society perceives harming women as more morally unacceptable, suggests that gender bias and harm considerations play a large role in shaping moral action.

So, even though people find harming others – or letting them suffer harm for a personal gain – to generally be an uncomfortable experience regardless of their gender, they are more willing to help/avoid harming women than they are men, sometimes by a rather substantial margin.

Now onto the fun part: explaining these findings. It doesn’t go nearly far enough as an explanation to note that “society condones harming men more than women,” as that just restates the finding; likewise, we only get so far by mentioning that people perceive men to have a higher pain tolerance than women (because they do), as that only pushes the question back a step to the matter of why men tolerate more pain than women. As for my thoughts, first, I think these findings highlight the importance of a modular understanding of psychological systems: our altruistic and moral systems are made up of a number of component pieces, each with a distinct function, and the piece that is calculating how much harm is generated is, it would seem, not the same piece deciding whether or not to do something about it. The obvious reason for this distinction is that alleviating harm to others isn’t always adaptive to the same extent: it does me more adaptive good to help kin relative to non-kin, friends relative to strangers, and allies relative to enemies, all else being equal. 

“Just stay out of it; he’s bigger than you”

Second, it might well be the case that helping men, on average, tends to pay off less than helping women. Part of the reason for that state of affairs is that female reproductive potential cannot be replaced quite as easily as male potential; male reproductive success is constrained by the number of available women much more than female potential is by male availability (as Chris Rock put it, “any money spent on dick is a bad investment“). As such, men might become particularly inclined to invest in alleviating women’s pain as a form of mating effort. The story clearly doesn’t end there, however, or else we would predict men being uniquely likely to benefit women, rather than both sexes doing similarly. This raises two additional possibilities to me: one of these is that, if men value women highly as a form of mating effort, that increased social value could also make women more valuable to other women in turn. To place that in a Game of Thrones example, if a powerful house values their own children highly, non-relatives may come to value those same children highly as well in the hopes of ingratiating themselves to – or avoiding the wrath of – the child’s family.

The other idea that comes to mind is that men are less willing to reciprocate aid that alleviated their pain because to do so would be an admission of a degree of weakness; a signal that they honestly needed the help (and might in the future as well), which could lower their relative status. If men are less willing to reciprocate aid, that would make men worse investments for both sexes, all else being equal; better to help out the person who would experience more gratitude for your assistance and repay you in turn. While these explanations might or might not adequately explain these preferential altruistic behaviors directed towards women, I feel they’re worthwhile starting points.

References: FeldmanHall, O., Dalgleish, T., Evans, D., Navrady, L., Tedeschi, E., & Mobbs, D. (2016). Moral chivalry: Gender and harm sensitive predict costly altruism. Social Psychological & Personality Science, DOI: 10.1177/1948550616647448

Sexism, Testing, And “Academic Ability”

When I was teaching my undergraduate course on evolutionary psychology, my approach to testing and assessment was unique. You can read about that philosophy in more detail here, but the gist of my method was specifically avoiding multiple-choice formats in favor of short-essay questions with unlimited revision ability on the part of the students. I favored this exam format for a number of reasons, chief among which was that (a) I didn’t feel multiple choice tests were very good at assessing how well students understood the material (memorization and good guessing does not equal understanding), and (b) I didn’t really care about grading my students as much as I cared about getting them to learn the material. If they didn’t grasp it properly on their first try (and very few students do), I wanted them to have the ability and motivation to continue engaging with it until they did get it right (which most eventually did; the class average for each exam began around a 70 and rose to a 90). For the purposes of today’s discussion, the important point here is that my exams were a bit more cognitively challenging than is usual and, according to a new paper, that means I had unintentionally biased my exams in ways that disfavor “historically underserved groups” like women and the poor.


What caught my eye about this particular paper, however, was the initial press release that accompanied it. Specifically, the authors were quoted as saying something I found, well, a bit queer:

“At first glance, one might assume the differences in exam performance are based on academic ability. However, we controlled for this in our study by including the students’ incoming grade point averages in our analysis,”

So the authors appear to believe that a gap in performance on academic tests arises independent of academic abilities (whichever those entail). This raised the immediate question in my mind of how one knows that abilities are the same unless one has a method of testing them. It seems a bit strange to say that abilities are the same on the basis of one set of tests (those that provided incoming GPAs), but then to continue to suggest that abilities are the same when a different set of tests provides a contrary result. In the interests of settling my curiosity, I tracked the paper down to see what was actually reported; after all, these little news blurbs frequently get the details wrong. Unfortunately, this one appeared to capture the author’s views accurately.

So let’s start by briefly reviewing what the authors were looking at. The paper, by Wright et al (2016), is based on data collected from three-years worth of three introductory biology courses spanning 26 different instructors, approximately 5,000 students, and 87 different exams.Without going into too much unnecessary detail, the tests were assessed by independent raters for how cognitively challenging they were, their format, and the students were classified according to their gender and socio-economic status (SES; as measured by whether they qualified for a financial aid program). In order to attempt and control for academic ability, Wright et al (2016) also looked at the freshman-year GPA of the students coming into the biology classes (based on approximately 45 credits, we are told). Because the authors controlled for incoming GPA, they hope to persuade the reader of the following:

This implies that, by at least one measure, these students have equal academic ability, and if they have differential outcomes on exams, then factors other than ability are likely influencing their performance.

Now one could argue that there’s more to academic ability than is captured by a GPA – which is precisely why I will do so in a minute – but let’s continue on with what the authors found first.

Cognitive challenging test were indeed, well, more challenging. A statistically-average male student, for instance, would be expected to do about 12% worse on the most challenging test in their sample, relative to the easiest one. This effect was not the same between genders, however. Again, using statistically-average men and women, when the tests were the least cognitively challenging, there was effectively no performance gap (about a 1.7% expected difference favoring men); however, when the tests were the most cognitively challenging, that expected gap rose to an astonishing expected…3.2% difference. So, while the gender difference just about nominally doubled, in terms of really mattering in any practical sense of the word, its size was such that it likely wouldn’t be noticed unless one was really looking for it. A similar pattern was discovered for SES: when the tests were easy, there was effectively no difference between those low or high in SES (1.3% favoring those higher); however, when the tests were about maximally challenging, this expected difference rose to about 3.5%. 

Useful for both spotting statistical blips and burning insects

There’s a lot to say about these results and how they’re framed within the paper. First, as I mentioned, they truly are minor differences; there are very few cases were a 1-3% difference in test scores is going to make-or-break a student, so I don’t think there’s any real reason to be concerned or to adjust the tests; not practically, anyway.

However, there are larger, theoretical issues looming in the paper. One of these is that the authors use the phrase “controlled for academic ability” so often that a reader might actually come to believe that’s what they did from simple repetition. The problem here, of course, is that the authors did not control for that; they controlled for GPA. Unfortunately for Wright et al’s (2016) presentation, those two things are not synonyms. As I said before, it is strange to say that academic ability is the same because one set of tests (incoming GPA) says they are while another set does not. The former set of tests appear to be privileged for no sound reason. Because of that unwarranted interpretation, the authors lose (or rather, purposefully remove) the ability to talk about how these gaps might be due to some performance difference. This is a useful rhetorical move if one is interested in doing advocacy – as it implies the gap is unfair and ought to be fixed somehow – but not if one is seeking the truth of the matter.

Another rather large issue in the paper is that, as far as I could tell, the authors predicted they would find these effects without ever really providing an explanation as for how or why that prediction arose. That is, what drove their expectation that men would outperform women and the rich outperform the poor? This ends up being something of a problem because, at the end of the paper, the authors do float a few possible (untested) explanations for their findings. The first of these is stereotype threat: the idea that certain groups of people will do poorly on tests because of some negative stereotype about their performance. This is a poor fit for the data for two reasons: first, while Wright et al (2016) claim that stereotype is “well-documented”, it actually fails to replicate (on top of not making much theoretical sense). Second, even if it was a real thing, stereotype threat, as it typically studied, requires that one’s sex be made salient prior to the test. As I encountered a total of zero tests during my entire college experience that made my gender salient, much less my SES, I can only assume that the tests in question didn’t do it either. In order for stereotype threat to work as an explanation, then, women and the poor would need to be under relative constant stereotype threat. In turn, this would make documenting and student stereotype threat in the first place rather difficult, as you could never have a condition where your subjects were not experiencing it. In short, then, stereotype threat seems like a bad fit.

The other explanations that are put forth for this gender difference are the possibility that women and poor students have more fixed views of intelligence instead of growth mindsets, so they withdraw from the material when challenged rather than improve (i.e., “we need to change their mindsets to close this daunting 2% gap), or the possibility that the test questions themselves are written in ways that subtly bias people’s ability to think about them (the example the authors raise is that a question written about applying some concept to sports might favor men, relative to women, as men tend to enjoy sports more). Given that the authors did have access to the test questions, it seems that they could have examined that latter possibility in at least some detail (minimally, perhaps, by looking at whether tests written by female instructors resulted in different outcomes than those written by male ones, or by examining the content of the questions themselves to see if women did worse on gendered ones). Why they didn’t conduct such analyses, I can’t say.

 Maybe it was too much work and they lacked a growth mindset

In summary, these very minor average differences that were uncovered could easily be chalked up – very simply – to GPA not being a full measure of a student’s academic ability. In fact, if the tests determining freshman GPA aren’t the most cognitively challenging (as one might well expect, given that students would have been taking mostly general introductory courses with large class sizes), then this might make the students appear to be more similar in ability than they actually were. The matter can be thought of using this stereotypically-male example (that will assuredly hinder women’s ability to think about it): imagine I tested people in a room with weights ranging from 1-15 pounds and asked them to curl each one time. This would give me a poor sense for any underlying differences in strength because the range of ability tested was restricted. Provided I were to ask them to do the same with weights ranging from 1-100 pounds the next week, I might conclude that it’s something about the weights – and not people’s abilities – when it came to figuring out why differences suddenly emerged (since I mistakenly believe I already controlled for their abilities the first time).

Now I don’t know if something like that is actually responsible, but if the tests determining freshman GPA were tapping the same kinds of abilities to the same degrees as those in the biology courses studied, then controlling for GPA should have taken care of that potential issue. Since controlling for GPA did not, I feel safe assuming there being some difference in the tests in terms of what abilities they’re measuring.

References: Wright, C., Eddy, S., Wenderoth, M., Abshire, E., Blankenbiller, M., & Brownell, S. (2016). Cognitive difficulty and format of exams predicts gender and socioeconomic gaps in exam performance of students in introductory biology courses. Life Science Education, 15.

Smoking Hot

If the view counts on previous posts have been any indication, people really do enjoy reading about, understanding, and – perhaps more importantly – overcoming the obstacles found on the dating terrain; understandably so, given its greater personal relevance to their lives. In the interests of adding some value to the lives of others, then, today I wanted to discuss some research examining the connection between recreational drug use and sexual behavior in order to see if any practical behavioral advice can be derived from it. The first order of business will be to try and understand the relationship between recreational drugs and mating from an evolutionary perspective; the second will be to take a more direct look at whether drug use has positive and negative effects when it comes to attracting a partner, and in what contexts those effects might exist. In short, will things like drinking and smoking make you smoking hot to others?

So far selling out has been unsuccessful, so let’s try talking sex

We can begin by considering why people care so much about recreational drug use in general: from historical prohibitions on alcohol to modern laws prohibiting the possession, use, and sale of drugs, many people express a deep concern over who gets to put what into their body at what times and for what reasons. The ostensibly obvious reason for this concern that most people will raise immediately is that such laws are designed to save people from themselves: drugs can cause a great degree of harm to users and people are, essentially, too stupid to figure out what’s really good for them. While perceptions of harm to drug users themselves no doubt play a role in these intuitions, they are unlikely to actually be whole story for a number of reasons, chief among which is that they would have a hard time explaining the connection between sexual strategies and drug use (and that putting people in jail probably isn’t all that good for them either, but that’s another matter). Sexual strategies, in this case, refer roughly to an individual’s degree of promiscuity: some people preferentially enjoy engaging in one or more short-term sexual relationships (where investment is often funneled to mating efforts), while others are more inclined towards single, long-term ones (where investment is funneled to parental efforts). While people do engage in varying degrees of both at times, the distinction captures the general idea well enough. Now, if one is the type who prefers long-term relationships, it might benefit you to condemn behaviors that encourage promiscuity; it doesn’t help your relationship stability to have lots of people around who might try to lure your mate away or reduce the confidence of a man’s paternity in his children. To the extent that recreational drug use does that (e.g., those who go out drinking in the hopes of hooking up with others owing to their reduced inhibitions), it will be condemned by the more long-term maters in turn. Conversely, those who favor promiscuity should be more permissive towards drug use as it makes enacting their preferred strategy easier.

This is precisely the pattern of results that Quintelier et al (2013) report: in a cross-cultural sample of Belgians (N = 476), Dutch (N = 298), and Japanese (N = 296) college students who did not have children, even after controlling for age, sex, personality variables, political ideology, and religiosity, attitudes towards drug use were still reliably predicted by participant’s sexual attitudes: the more sexually permissive one was, the more they tended to approve of drug use. In fact, sexual attitudes were the best predictors of people’s feelings about recreational drugs both before and after the controls were added (findings which replicated a previous US sample). By contrast, while the non-sexual variables were sometimes significant predictors of drug views after controlling for sexual attitudes, they were not as reliable and their effects were not as large. This pattern of results, then, should yield some useful predictions about how drug use effects your attractiveness to other people: those who are looking for short-term sexual encounters might find drug use more appealing (or at least less off-putting), relative to those looking for long-term relationships.

“I pronounce you man and wife. Now it’s time to all get high”

Thankfully, I happen to have a paper on hand that speaks to the matter somewhat more directly. Vincke (2016) sought to examine how attractive brief behavioral descriptions of men were rated as being by women for either short- or long-term relationships. Of interest, these descriptions included the fact that the man in question either (a) did not, (b) occasionally, or (c) frequently smoke cigarettes or drink alcohol. A sample of 240 Dutch women were recruited and asked to rate these profiles with respect to how attractive the men in question would be for either a casual or committed relationship and whether they thought the men themselves were more likely to be interested in short/long-term relationships.

Taking these in reverse order, the women rated the men who never smoked as somewhat less sexually permissive (M = 4.31, scale from 1 to 7) than those who either occasionally or frequently did (Ms = 4.83 and 4.98, respectively; these two values did not significantly differ). By contrast, those who never drank or occasionally did were rated as being comparably less permissive (Ms = 4.04) than the men who drank frequently (M = 5.17). Drug use, then, did effect women’s perceptions of men’s sexual interests (and those perceptions happen to match reality, as a second  study with men confirmed). If you’re interested in managing what other people think your relationship intentions are, then, managing your drug use accordingly can make something of a difference. Whether that ended up making the men more attractive is a different matter, however.

As it turns out, smoking and drinking appear to look distinct in that regard: in general, smoking tended to make men look less attractive, regardless of whether the mating context was short- or long-term, and frequent smoking was worse than occasional smoking. However, the decline in attractiveness from smoking was not as large in short-term contexts. (Oddly, Vincke (2016) frames smoking as being an attractiveness benefit in short-term contexts within her discussion when it’s really just less of a cost. The slight bump seen in the data is neither statistically or practically significant) This pattern can be seen in the left half of the author’s graph. By contrast – on the right side – occasional drinkers were generally rated as more attractive than men who never or frequently drank across conditions across both short- and long-term relationships. However, in the context of short-term mating, frequent drinking was rated as being more attractive than never drinking, whereas this pattern reversed itself for long-term relationships. As such, if you’re looking to attract someone for a serious relationship, you probably won’t be impressing them much with your ability to do keg stands of liquor, but if you’re looking for someone to hook up with that night it might be better to show that off than sip on water all evening.

Cigarettes and alcohol look different from one another in the attractiveness domain even though both might be considered recreational drug use. It is probable that what differentiates them here is their effects on encouraging promiscuity, as previously discussed. While people are often motivated to go out drinking in order to get intoxicated, lose their inhibitions, and have sex, the same cannot usually be said about smoking cigarettes. Singles don’t usually congregate at smoking bars to meet people and start relationships, short-term or otherwise (forgoing for the moment that smoking bars aren’t usually things, unless you count the rare hookah lounges). Smoking might thus make men appear to be more interested in casual encounters because it cues a more general interest in short-term rewards, rather than anything specifically sexual; in this case, if one is willing to risk the adverse health effects in the future for the pleasure cigarettes provide today, then it is unlikely that someone would be risk averse in other areas of their life.

If you want to examine sex specifically, you might have picked the wrong smoke

There are some limitations here, namely that this study did not separate women in terms of what they were personally seeking in terms of relationships or their own interests/behaviors when it comes to engaging in recreational drug use. Perhaps these results would look different if you were to account for women’s smoking/drinking habits. Even if frequent drinking is a bad thing for long-term attractiveness in general, a mismatch with the particular person you’re looking to date might be worse. It is also possible that a different pattern might emerge if men were assessing women’s attractiveness, but what differences those would be are speculative. It is unfortunate that the intuitions of the other gender didn’t appear to be assessed. I think this is a function of Vincke (2016) looking for confirmatory evidence for her hypothesis that recreational drug use is attractive to women in short-term contexts because it entails risk, and women value risk-taking more in short-term male partners than long-term ones. (There is a point to make about that theory as well: while some risky activities might indeed be more attractive to women in short-term contexts, I suspect those activities are not preferred because they’re risky per se, but rather because the risks send some important cue about the mate quality of the risk taker. Also, I suspect the risks need to have some kind of payoff; I don’t think women prefer men who take risks and fail. Anyone can smoke, and smoking itself doesn’t seem to send any honest signal of quality on the part of the smoker.)

In sum, the usefulness of these results for making any decisions in the dating world is probably at its peak when you don’t really know much about the person you’re about to meet. If you’re a man and you’re meeting a woman who you know almost nothing about, this information might come in handy; on the other hand, if you have information about that woman’s preferences as an individual, it’s probably better to use that instead of the overall trends. 

References: Quintelier, K., Ishii, K., Weeden, J., Kurzban, R., & Braeckman, J. (2013). Individual differences in reproductive strategy are related to views about recreational drug use in Belgium, the Netherlands, and Japan. Human Nature, 24, 196-217.

Vincke, E. (2016). The young male cigarette and alcohol syndrome: Smoking and drinking as a short-term mating strategy. Evolutionary Psychology, 1-13.