No Sexism In SCRABBLE

My last couple of posts have focused primarily on the topic of group differences and on understanding how they might come to exist. Some of the most commonly-advanced explanations for these differences concern discrimination – explicit or implicit – that serves to keep otherwise interested and qualified people out of arenas they would like to compete in. For example, few men might want to be nurses because male nurses aren’t considered for positions even if they’re qualified because of a social stigma against men in that area. If that was the explanation for these group differences, it would represent a wealth of untapped social value achievable by reducing or removing those discriminatory boundaries. On the other hand, if discrimination is not the cause of those differences, a lot of time and energy could be invested into chasing down a boogeyman without yielding much in the way of value for anyone.

Unfortunately, as we saw last time (and other times), research seeking to test these explanations can be designed or interpreted in ways that make them resilient to falsification. If the hypothesized effect attributable to discrimination is observed, it is counted as evidence consistent with the explanation; when the effect isn’t observed, however, it is not counted as evidence against the proposal. They are sure the discrimination is there; they just didn’t dig deep enough to find it. This practice can be maintained effectively in many domains because of the fuzzy nature of performance within them. That is, it’s not always clear which person would make a better manager or professor when it comes time to make a hiring decision or assess performance, so different rates of hiring or promotions cannot be clearly related to different behavior.

And if the quality of your work can’t be assessed, it also means you can never be said to fail at your job

One way of working that fuzziness out of the equation is to turn towards domains where more objective measures of performance can be obtained. While it might be difficult to say for certain that one person would make a superior manager to another – especially when they are closely matched in skills – it is quite a lot easier to see if they can complete a task with objective performance criteria, such as winning in a video game or performing pull-ups. In realms of objective performance, it doesn’t matter if people like you or not; your abilities are being tested against reality. Accordingly, domains with more objective performance criteria make for appealing research tools when it comes to assessing and understanding group differences.

On that note, Moxley, Ericsson, & Tuffiash (2017) report some interesting information concerning the board game SCRABBLE. For the handful of you who might not know what SCRABBLE is, it’s a game where each player randomly selects a number of tiles with letters on them, then uses those tiles to spell words: the larger the word or the harder the letters are to utilize, the more points the player receives. The player with the most points after the tiles have been used up wins. As it turns out, men tend to be over-represented in the upper tiers of SCRABBLE performance. Within the highest-performing competitive SCRABBLE divisions, 86% of the players are male, while only 31% of the players in the lowest-performing divisions are. This patterns holds even though most of the competitive SCRABBLE players are women. Indeed, when regular people are asked about whether they would expect more male or female SCRABBLE champions, the intuition seems to be that women should be more common (despite, for context, all 10 of the last world champions having been male).

How is that sex difference in performance to be explained? In this instance, discrimination looks to be an odd explanation: competitive SCRABBLE tournaments do not present clear barriers to entry and women appear to be at least as interested – if not more so – in SCRABBLE than men are, as inferred from participation rates. Moreover, people even seem to expect women would do better than men in that field, so an explanation along the lines of stereotype threat doesn’t work well either. According to the research of Moxley, Ericsson, & Tuffiash (2017), the explanation for most of that sex difference in performance does, in fact, relate to varying male and female interests, but perhaps not those directed at playing SCRABBLE itself. While I won’t discuss every part of the studies they undertook, I wanted to highlight some general points of this research because of how well it can highlight the difficulty and nuance in understanding sex differences and their relation to performance within a given field.

Even this vicious field of battle

The general methodology employed by the researchers involved surveying participants at National SCRABBLE competitions in 2004 and 2008 about their overall level of practice each year, both in terms of time spent studying alone and practicing seriously with others. These responses were then examined in the context of the player’s competitive SCRABBLE rating. The first study turned up several noteworthy relationships. As expected, women tended to have lower ratings than men (d = -0.74). However, it was also found that different types of SCRABBLE practice had varying impacts on player ratings. In this case, studying vocabulary had a negative impact on performance, while time spent analyzing past games and doing anagrams had a positive impact. This means that just asking people about how much they practiced SCRABBLE is not enough of a fine-tuned question for good predictive accuracy concerning performance. In this case, the practice questions asked about were unable to account for the entirety of the gender difference in performance, but they did reduce it somewhat.

This led the researchers to ask more detailed questions about SCRABBLE players’ practice in their second study. As before, women tended to have lower ratings than men (d = -0.69), but once the more refined questions about practice and experience were accounted for, there was no longer a direct effect of gender on rating. This would suggest that the performance advantage men had in SCRABBLE can be largely attributed to their spending more time engaged in solitary practice that benefits performance, while women tended to spend more time playing SCRABBLE with others; a behavior which did not yield comparable performance benefits.

The final step in this analysis was to figure out why men and women spent different amounts of time engaged in the types of practice they did. To do so, the players’ responses about how relevant, enjoyable, and effortful various types of practice felt were assessed. In order, the players felt tournament experience was the most important for improving their skills, then playing SCRABBLE itself, followed last by other types of word games. On that front, perceptions weren’t quite accurate. A similar pattern emerged in terms of which activities were rated as most enjoyable. However, there was a sex difference in that women rated playing SCRABBLE outside of tournaments as more enjoyable than men, and men rated SCRABBLE-specific practice (like anagrams) as more enjoyable than women.

Taken together, men tended to find the most-effective practice methods more enjoyable than women, and so engaged in them more. This differential involvement in effective practice in turn explained the sex difference in player rankings. Nothing too shocking, but reality often isn’t.

Published in the journal of, “I’m sorry; did you say something?”

What we see in this research is an appreciable sex difference in performance resulting from varying male and female interests, but those interests themselves are not necessarily the most obvious targets for investigation. If you were to just ask men and women whether they were interested in SCRABBLE, you might find that women had a higher average interest. If you were to just ask about how much time they spent practicing, you might not observe a sex difference capable of explaining the differences in performance. It wouldn’t be until you asked specifically about their interests in particular types of practice and understood how those related to eventual performance that you end up with a better picture of that performance gap. In this case, it seems to be the case that the sex difference is largely the product of men being more interested in specific types of practice that are ultimately more productive when it comes to improving performance. The corollary point to that is that if you were trying to reduce the male-female performance gap in SCRABBLE, if your explanation for that gap was that women are being discriminated against and so sought to reduce discrimination in the field, you’d probably do nothing to help even out the scores (though you might achieve some social maligning). 

Thankfully this kind of analysis can be reasonably undertaken in a realm where performance can be objectively assessed. If you were to think about trying this same analysis with respect to, say, the relative distribution of men and women in STEM fields, you’re in for a much rockier experience where it’s not clear how certain interests relate to ultimate performance.

References: Moxley, J., Ericsson, A., & Tuffiash, M. (2017). Gender differences in SCRABBLE performance and associated engagement in purposeful practice activities. Psychological Research, DOI 10.1007/s00426-017-0905-3

Imagine If The Results Went The Other Way

One day, three young children are talking about what they want to be when they get older. The first friend says, “I love animals, so I want to become a veterinarian.” The second says, “I love computers, so I want to become a programmer.” The third says, “I love making people laugh, so I want to become a psychology researcher.” Luckily for all these children, they all end up living a life that affords them the opportunity to pursue their desires, and each ends up working happily in the career of their choice for their entire adult life.

The first question I’d like to consider is whether any of those children made choices that were problematic. For instance, should the first child have decided to help animals, or perhaps should they have put their own interests aside and pursued another line of work because of their sex and the current sex-ratio of men and women in that field? Would your answer change if you found out the sex of each of the children in question? Answer as if the second child was a boy, then think about whether your answer would change if you found out she was a girl.

Well if you wanted to be a vet, you should have been born a boy

This hypothetical example should, hopefully, highlight a fact that some people seem to lose track of from time to time: broad demographic groups are not entities themselves; only made up of their individual members. Once one starts talking about how gender inequality in professions ought to be reduced – such that you see a greater representation of 50/50 men and women across a greater number of fields – you are, by default, talking about how some people need to start making choices less in line with their interests, skills, and desires to reach that parity. This can end up yielding strange outcomes, such as a gender studies major telling a literature major she should have gone into math instead. 

Speaking of which, a paper I wanted to examine today (Riegle-Crumb, King, & Moore, 2016) begins laying on the idea of gender inequality across majors rather thick. Unless I misread their meaning, they seem to think that gender segregation in college majors ought to be disrupted and, accordingly, sought to understand what happens to men and women who make non-normative choices in selecting a college major, relative to their more normative peers. Specifically, they set out to examine what happens to men who major both in male- and female-dominated fields: are they likely to persist in their chosen field of study in the same or different percentages? The same question was asked of women as well. Putting that into a quick example, you might consider how likely a man who initially majors in nursing is to switch or stay in his program, relative to one who majors in computer science. Similarly, you might think about the fate of a woman who majors in physics, compared to one who majors in psychology.

The authors expected that women would be more likely to drop out of male-dominated fields because they encounter a “chilly” social climate there and face stereotype threat, compared to their peers in female-dominated fields. By contrast, men were expected to drop out of female-dominated fields more often as they begin to confront the prospect of earning less money in the future and/or lose social status on account of emasculation brought on by their major (whether perceived or real).

To test these predictions, Riegle-Crumb, King, & Moore (2016) examined a nationally-representative sample of approximately 3,700 college students who had completed their degree. These students had been studied longitudinally, interviewed at the end of their first year of college in 2004, then again in 2006 and 2009. A gender atypical major was coded as one in which the opposite sex compromised 70% or more of the major. In the sample being examined, 14% of the males selected a gender-atypical field, while 4% of women did likewise. While this isn’t noted explicitly, I suspect some of that difference might have to do with the relative size of certain majors. For instance, psychology is one of the most popular majors in the US, but also happened to fall under the female-dominated category. That would naturally yield more men than women choosing a gender atypical major if the pattern continued into other fields.

Can’t beat that kind of ratio in the dating pool, though

Moving on to what was found, the researchers were trying to predict whether people would switch majors or not. The initial analysis found that men in male-typical majors switched about 39% of the time, compared to the 63% of men who switched from atypical majors. So the men in atypical fields were more likely to switch. There was a different story for the women, however: those in female-typical majors switched 46% of the time, compared to 41% who switched in atypical fields. The latter difference was neither statistically or practically significant. Unsurprisingly, for both men and women, those most likely to switch had lower GPAs than those who stayed, suggesting switching was due, in part, to performance.

When formally examined with a number of control variables (for social background and academic performance) included in the model, men in gender atypical fields were about 2.6 times as likely to switch majors, relative to those in male-dominated ones. The same analysis run for women found that those in atypical majors were about 0.8 times as likely to switch majors as those in female-dominated ones. Again, this difference wasn’t statistically significant. Nominally, however, women in atypical fields were more likely to stay put.

What do the authors make of this finding? Though they note correctly that their analysis says nothing of the reasons for the switch, they view the greater male-atypical pattern of switching as consistent with their expectations. I think this is probably close to the truth: as a greater proportion of a man’s future success is determined by his ability to provision mates and his social status, we might expect that men tend to migrate from majors with a lower future financial payoff to those that have a larger one. Placing that into a personal example, I might have wanted to be a musician, but the odds of landing a job as a respected rockstar seemed slim indeed. Better that I got a degree in something capable of paying the bills consistently if I care about money.

By contrast, the authors also correctly note that they don’t find evidence consistent with their prediction that women in gender-atypical fields would switch more often. This does not, however, cause them to abandon the justifications for their prediction. As far as I can tell, they still believe that factors like a chilly climate and stereotype threat are pushing women out of those majors; they just supplement that expectation by adding on that a number of factors (like the aforementioned financial ones) might be keeping them in, and the latter factors are either more common or influential (though that certainly makes you wonder why women tend to choose lower-paying fields in greater numbers the first place).

Certainly worth a 20-year career in a field you hate

This strikes me as kind of a fool-proof strategy for maintaining a belief in the prospect of nefarious social forces doing women harm. To demonstrate why, I’d like to take this moment to think about what people’s reactions to these findings might have been if the patterns for men and women were reversed. If it turned out that women in male-dominated majors were more likely to switch than their peers in female-dominated majors, would there have been calls to address the clear sexism causally responsible for that pattern? I suspect that answer is yes, judging from reactions I’ve seen in the past. So, if that result was found, the authors could point a finger at the assumed culprits. However, even when that result was not found, they can just tack on other assumptions (women remain in this major for the money) that allows the initial hypothesis of discrimination to be maintained in full force. Indeed, they end their paper by claiming, “Gender segregation in fields of study and related occupations severely constrains the life choices and chances of both women and men,” demonstrating a full commitment to being unphased by their results.

In other words, there doesn’t seem to be a pattern of data that could have been observed capable of falsifying the initial reasons these expectations were formed. Even nominally contradictory data appears to have been assimilated into their view immediately. Now I’m not going to say it’s impossible that there are large, sexist forces at work trying to push women out of gender atypical fields that are being outweighed by other forces pulling in the opposite direction; that is something that could, in theory, be happening. What I will say is that granting that possibility makes the current work a poor test of the original hypotheses, since no data could prove it wrong. If you aren’t conducting research capable of falsifying your ideas – asking yourself, “what data could prove me wrong?” – then you aren’t engaged in rigorous science. 

References: Riegle-Crumb, C., King, B., & Moore, C. (2016). Do they stay or do they go? The switching decisions of individuals who enter gender atypical college majors. Sex Roles, 74, 436-449.

Not-So-Leaky Pipelines

There’s an interesting perspective many people take when trying to understand the distribution of jobs in the world, specifically with respect to men and women: they look at the percentage of men and women in a population (usually in terms of country-wide percentages, but sometimes more localized), make note of any deviations from those percentages in terms of representation in a job, and then use those deviations to suggest that certain desirable fields (but not usually undesirable ones) are biased against women. So, for instance, if women make up 50% of the population but only represent 30% of lawyers, there are some who would conclude this means the profession (and associated organizations) is likely biased against women, usually because of some implicit sexism (as evidence of explicit and systematic sexism in training or hiring practices is exceptionally hard to come by). Similar methods have been used when substituting race for gender as well.

Just another gap, no doubt caused by sexism

Most of the ostensible demonstrations of this sexism issue are wanting, and I’ve covered a number of these examples before (see here, here, here, and here). Simply put, there are a lot of factors in the world that determine where people ultimately end up working (or whether they’re working at all). Finding a consistent gap between groups tells you something is different, just not what. As such, you don’t just get to assume that the cause of the difference is sexism and call it a day. My go-to example in that regard has long been plumbing. As a profession, it is almost entirely male dominated: something like 99% of the plumbers in the US are men. That’s as large of a gender gap as you could ask for, yet I have never once seen a campaign to get more women into plumbing or complaints about sexism in the profession keeping otherwise-interested women out. Similarly, men make up about 96% of the people shot by police, but the focus on police violence has never been on getting officers to shoot fewer men per se. In those cases, most people seem to recognize that factors other than sex are the primary determinants of the observed sex differences. Correlation isn’t causation, and maybe women aren’t as interested in digging around through human waste or committing violent felonies as men are. Not to say that many men are interested, just that more of those who are end up being men.

If that was the case and these sex differences aren’t caused by sexism, any efforts that sought to “fix” the gap by focusing on sexism would ultimately be unsuccessful. At the risk of saying something too obvious, you change outcomes by changing their causes; not unrelated issues. If we have the wrong idea as to what is causing an outcome, we end up wasting time and money (which often does not belong to us) trying to change it and accomplishing very little in the process (outside of getting people annoyed at us for wasting their time and money).

Today I wanted to add to that pile of questionable claims of sexism concerning an academic neighbor to psychology: philosophy. Though I was unaware of this debate, there is apparently some contention within the field concerning the perceived under-representation of women. As is typical, the apparent under-representation of women in this field has been chalked up to sexist biases keeping women discouraged and out of a job. To be clear about things, some people are looking at the percentage of men and women in the field of philosophy, noting that it differs from their expectations (whatever those are and however they were derived), calling it under-representation because of those expectations, and then further assuming a culprit in the form of sexism. As it turns out, the data has something to say about that.

It also has some great jokes about Polish people if you’re a racist.

The data in question come from a paper by Allen-Hermanson (2017), which examined sex differences in tenure-track hiring and academic publishing in philosophy departments. The reasoning behind this line of research was that if insidious forces are at work against women in philosophy departments, we ought to expect something of a leaky pipeline: women should not be as successful as men at landing desirable, tenure-track jobs, relative to the rates at which each sex earn philosophy degrees. So, if women earned, say, 40% of the philosophy PhDs during the last year, we might expect that they get 40% of the tenure-track jobs in the next, all else being equal. Across the 10 year period examined (2005-2014), there were three years in which women were hired very slightly below their relative percentage into the tenure-track jobs (and by “very slightly” I’m talking in range of about 1-2%), one year in which it was dead even, and during the remaining six years women were hired at above the rate which would be expected by much more substantial margins (in the range of 5-10%).

Putting some rough numbers to that, women earned about 28% of the PhDs and received about 36% of the jobs in the most recent hiring seasons. It seems, then, women tended to be over-represented in those positions, on average. Other data discussed in the paper corresponds to those findings, again suggesting that women had about a 25% advantage over men in finding desirable positions (in terms of less desirable positions, men and women were hired in about equal numbers).

This finding is made all the stranger by Allen-Hermanson (2017) noting that male and female degree holders differed with respect to how often they published. On average, the new tenure-track female candidates who had never held such a position before had 0.77 publications. The comparable male number was 1.37. Of those who secured a job in 2012-2013, men averaged 2.4 publications to women’s 1.17. Not only are the men publishing about twice as much, then, but they’re also modestly less successful at landing a job (and this effect did not appear to be driven by particularly prolific publishers). While one could possibly make the case that maybe female publications are in some sense higher qualitythat remains to be seen. One could more easily make the case that female candidates were held to lower standards than male ones.

As the data currently stand, I can’t imagine many people will be making a fuss about them and crying sexism. Perhaps the men with the degrees went out to seek work elsewhere and that explains why women are over-represented. Perhaps there are other causes. The world is a complicated place, after all. The point here is that there won’t be talk about how philosophy departments are biased against men, just like there wasn’t much talk I saw last time research found a much larger academic bias in favor of women, holding candidate quality constant. I think that is largely because the data apparently favor women with respect to hiring. If the results had run in the opposite direction, I can imagine that a lot more noise would have been made about them and many people would be getting scolded right now about their tolerance of sexism. But that’s just an intuition.

“Now, if you’ll excuse me, I’m off to find bias against my group somewhere else”

When asking a question of under-representation, the most pressing matter should always be, “under-represented with respect to what expectation?” In order to say that a group is under-represented, you need to make it clear what the expected degree of representation is as well as why. We shouldn’t expect that men and women be killed by police in equal numbers unless we also expect that both groups behave more-or-less identically. We similarly shouldn’t expect that men and women enter into certain fields in the same proportion unless they have identical sets of interests. On the other hand, if the two groups are different with respect to some key factor that determines an outcome, such as interests, using sex itself is just a poor variable choice. Compared to interest in fixing toilets (and other such relevant factors), I imagine sex itself uniquely predicts very little about who ultimately ends up becoming a plumber. If we can use those better, more directly-relevant factors, we should. You don’t build your predictive model with irrelevant factors; not if accuracy is your goal, in any case.

References: Allen-Hermanson S. (2017). Leaking pipeline myths: In search of gender effects on the job market and early career publishing in philosophy. Frontiers in Psychology, 8, doi: 10.3389/fpsyg.2017.00953

Understanding Sex In Advertising

When people post videos on YouTube, one major point of interest for content creators and aggregators is to capture as much attention as possible. Your video is adrift in a sea of information and you’re trying to get as many eyes/clicks on your work as possible. In that realm, first impressions are all important: you want your video to have an attention-grabbing thumbnail image, as that will likely be the only thing viewers see before they actually click (or don’t) on it. So how do people go about capturing attention in that realm? One popular method is to ensure their thumbnail has a very emotive expression on it; a face of shock, embarrassment, stress, or any similar emotion. That’s certainly one way of attracting attention: trying to convince people there is something worth looking at, not unlike articles titled along the lines of five shocking tips for a better sex life (and number 3 will blow your mind!). Speaking of sex, that’s another popular method of grabbing attention: it’s fairly common for video thumbnails to feature people or body parts in various stages of undress. Not much will pull eyes towards a video like the promise of sex (and if you’re feeling an urge to click on that link, you’ll have experienced exactly what I’m talking about).

Case in point: most of that content is unrelated to the featured women

If sex happens to be attention grabbing, the natural question arises concerning what you might do with that attention once you have it. Much of the time, that answer will involve selling some good or service. In other words, sex is used as a form of advertising to try and sell things. “If you enjoyed that picture of a woman wearing a thong, you’ll surely love our reasonably-costed laptops!”. Something along those lines, anyway. Provided that’s your goal, lots of questions naturally start to crop up: How effective is sex at these goals? Does it capture attention well? Does it help people notice and remember your product or brand? Are those who viewed your sexy advert more likely to buy the product you’re selling? How do other factors – the sex of the person viewing the ad – contribute to your success in these realms?

These are some of the questions examined in a recent meta-analysis by Wirtz, Sparks, & Zimbres (2017). The researchers searched the literature and found about 80 studies, representing about 18,000 participants. They sought to find out what effects featuring sexually provocative material had, on average (defined in terms of style of dress, sexual behavior, innuendo, or sexual embeds, which is where hidden messages or images are placed within the ad, like the word “sex” added somewhere to the picture, which is something people apparently think is a good idea sometimes). These ads had to have been compared against a comparable, non-sexual ad for the same product to be included in the analysis to determine which was more effective.

The effectiveness of these ads were assessed across a number of domains as well, including ad recognition (in aided and unaided contexts), whether the brand being advertised in the ad could be recalled (i.e., were people paying attention to just the sex, or did they remember the product?), the positive or negative response people had to the ad, what people thought about the brand being advertised with sex, and whether the ad actually got them interested in purchasing the product (does sex sell?).

Finally, a number of potentially moderating factors that might influence these effects were considered. The first of these was gender: did these ads have different impacts on men and women? Others factors included the gender of the model used in the advertisement, the date the article was published (to see if attitudes shifted over time), the sample used (college students or not), and – most interestingly – product/ad congruity: did the type of product being advertised matter when it came to whether sex was effective? Perhaps sex might help sell a product like sun-tan lotion (as the beach might be a good place to pick up mates), but be much less effective for selling, say, laptops.

Maybe even political views

In terms of capturing attention, sex works. Of the 20 effects looking at the recall for ads, the average size was d = .38. Interesting, this effect was slightly larger for the congruent ads (d = .45), but completely reversed for the incongruent ones (d = -.45). Sex was good at getting people to remember ads selling a sex-related product, but not just generally useful. That said, they seemed better at getting people to remember just the ads. When the researchers turned to the matter of whether the brands within the ads were more likely to be recalled, the 31 effects looking at brand recognition turned out to barely break zero (d = .09). While sex might be attention-grabbing, it didn’t seem especially good at getting people to remember the objects being sold.

Regarding people’s attitudes towards the ads, sex seems like something of a wash (d = -.07). Digging a little deeper revealed a more nuanced pictured of these reactions, though: while sexual ads seemed to be a modest hit with the men (d = .27), they had the opposite effect on women (d = -.38). Women seemed to dislike the ads modestly more than men liked them, as sexual strategies theory would suggest (for the record, the type of model being depicted didn’t make much of a difference. In order, people liked males models the least (d = -.28), then female models (d = -.20), and couples were mildly positive, d = .08).

Curiously, both the men and women seemed to be agreement regarding their stance towards brands that used sex to sell things: negative, on the whole (d – =.22). For women, this makes some intuitive sense: they didn’t see to be a fan of the sexual ads, so they weren’t exactly feeling too ingratiated towards the brand itself. But why were the men negatively inclined towards the brand if they were favorably inclined towards the ads? I can only speculate on that front, but I assume it would have something to do with their inevitable disappointment: either that the brands were promising on sex the male customers likely knew they couldn’t deliver on, or perhaps the men simply wanted to enjoy the sex part and the brand itself ended up getting in their way. I can’t imagine men would be too happy with their porn time being interrupted by an ad for toilet paper or fruit snacks mid-video.

Finally, turning the matter of purchase intentions – whether the ads encouraged people to want to buy the product or not – it seemed that sex didn’t really sell, but it didn’t really seem to hurt, either (d = .01). One interesting exception in that realm was that sex appeals were actually less likely to get people to buy a product when the product being sold was incongruent with the sexual appeal (d = -.24). Putting that into a simple example, the phrase “strip club buffet” probably doesn’t wet many appetites, and wouldn’t be a strong selling point for such a venue. Sex can be something of a disease vector, and associating your food with that might illicit more than a bit of disgust.

“Oh good, I was starving. This seems like as good a place as any”

As I’ve noted before, context matching matters in advertising. If you’re looking to sell people something that highlights their individuality, then doing so in a mating context works better than in a context of fear (as animals aren’t exactly aiming to look distinct when predators are nearby). The same seems to hold for using sex. While it might be useful for getting eyes on your advertisement, sex is by no mean guaranteed to ensure that people like what they see once you have their attention. In that regard, sex – like any other advertising tool – needs to be used selectively, targeting the correct audience in the correct context if it’s going to succeed at increasing people’s interest in buying. Sex in general doesn’t sell. However, it might prove more effective for those with more promiscuous attitudes than those with more monogamous ones; it might prove useful if advertising a product related to sex or mating, but not useful for selling domain names (like the old GoDaddy commercials; coincidentally, GoDaddy was also the brand I used to register this site); it might work better if you associate your product with things that lead to sex (like status), rather than sex itself. These are all avenues worth pursuing further to see when, where, and why sex works or fails.

That said, it is still possible that sex might prove useful, even in some inappropriate contexts. Consider the following hypothetical example: people will consider buying a product only after they have seen an advertisement for it. Advertisement X isn’t sexual, but when paired with the product will increase people’s intentions to buy it by 10%. However, it will also not really get noticed by many people, as the content is bland. By contrast, advertisement Y is sexual, will decrease people’s intentions to buy a product by 10%, but will also get four-times as many eyes on it. The latter ad might well be more successful, as it will capture the eye of more potential customers that may still buy the product despite the inappropriate use of sexWhile targeting advertisements might be more effective, the attention model of advertising shouldn’t be ruled out entirely, especially if targeting advertising would prove too cumbersome.

References: Wirtz, J., Sparks, J., & Zimbres, T. (2017). The effect of exposure to sexual appeals in advertisements on memory, attitude, and purchase intention: A meta-analytic review. International Journal of Advertising, https://doi.org/10.1080/02650487.2017.1334996

 

Mistreated Children Misbehaving

None of us are conceived or born as full adults; we all need to grow and develop from single cells to fully-formed adults. Unfortunately – for the sake of development, anyway – the future world you will find yourself in is not always predictable, which makes development a tricky matter at times. While there are often regularities in the broader environment (such as the presence or absence of sunlight, for instance), not every individual will inhabit the same environment or, more precisely, the same place in their environment. Consider two adult males, one of whom is six-feet tall and 230 pounds of muscle, and the other being five-feet tall and 110 pounds. While the dichotomy here is stark, it serves to make a simple point: if both of these males developed in a psychological manner that led them to pursue precisely the same strategies in life – in this case, say, one involving aggressive contests for access to females – it is quite likely that the weaker male will lose out to the stronger one most (if not all) of the time. As such, in order to be more-consistently adaptive, development must be something of a fluid process that helps tailor an individual’s psychology to the unique positions they find themselves in within a particular environment. Thus, if an organism is able to use some cues within their environment to predict their likely place in it in the future (in this case, whether they would grow large or small), their development could be altered to encourage their pursuit of alternate routes to eventual reproductive success. 

Because pretending you’re cut out for that kind of life will only make it worse

Let’s take that initial example and adapt it to a new context: rather than trying to predict whether one will grow up weak or strong, a child is trying to predict the probability of receiving parental investment in the future. If parental investment is unlikely to be forthcoming, children may need to take a different approach to their development to help secure the needed resources on their own, sometimes requiring their undertaking risky behaviors; by contrast, those children who are likely to receive consistent investment might be relatively less-inclined to take such risky and costly matters into their own hands, as the risk vs. reward calculations don’t favor such behavior. Placed in an understandable analogy, a child who estimates they won’t be receiving much investment from their parents might forgo a college education (and, indeed, even much of a high-school one) because they need to work to make ends meet. When you’re concerned about where your next meal is coming from there’s less time in your schedule for studying and taking out loans to not be working for four years. By contrast, the child from a richer family has the luxury of pursuing an education likely to produce greater future rewards because certain obstacles have been removed from their path.

Now obviously going to college is not something that humans have psychological adaptations for – it wasn’t a recurrent feature of our evolutionary history as a species – but there are cognitive systems we might expect to follow different developmental trajectories contingent on such estimations of one’s likely place in the environment; these could include systems judging the relative attractiveness of short- vs long-term rewards, willingness to take risks, pursuit of aggressive resolutions to conflicts, and so on. If the future is uncertain, saving for it makes less than taking a smaller reward in the present; if you lack social or financial support, being willing to fight to defend what little you do have might sound more appealing (as losing that little bit is more impactful when you won’t have anything left). The questions of interest thus becomes, “what cues in the environment might a developing child use to determine what their future will look like?” This brings us to the current paper by Abajobir et al (2016).

One potential cue might be your experiences with maltreatment while growing up, specifically at the hands of your caregivers. Though Abajobir et al (2016) don’t make the argument I’ve been sketching out explicitly, that seems to be the direction their research takes. They seem to reason (implicitly) that parental mistreatment should be a reliable cue to the future conditions you’re liable to encounter and, accordingly, one that children could use to alter their development. For instance, abusive or neglectful parents might lead to children adopting faster life history strategies involving risk-taking, delinquency, and violence themselves (or, if they’re going the maladaptive explanatory route, the failure of parents to provide supporting environments could in some way hinder development from proceeding as it usually would, in a similar fashion to not having enough food growing up might lead to one being shorter as an adult. I don’t know which line the authors would favor from their paper). That said, there is a healthy (and convincing) literature consistent with the hypothesis that parental behavior per se is not the cause of these developmental outcomes (Harris, 2009), but rather that it simply co-occurs with them. Specifically, abusive parents might be genetically different from non-abusive ones and those tendencies could get passed onto the children, accounting for the correlation. Alternatively, parents that maltreat their children might just happen to go together with children having peer groups growing up more prone to violence and delinquency themselves. Both are caused by other third variables.

Your personality usually can’t be blamed on them; you’re you all on your own

Whatever the nature of that correlation, Abajobir et al (2016) sought to use parental maltreatment from ages 0 to 14 as a predictor of later delinquent behaviors in the children by age 21. To do so, they used a prospective cohort of children and their mothers visiting a hospital between 1981-83. The cohort was then tracked for substantiated cases of child maltreatment reported to government agencies up to age 14, and at age 21 the children themselves were surveyed (the mothers being surveyed at several points throughout that time). Out of the 7200 initial participants, 3800 completed the 21-year follow up. At that follow up point, the children were asked questions concerning how often they did things like get excessively drunk, use recreational drugs, break the law, lie, cheat, steal, destroy the property of others, or fail to pay their debts. The mothers were also surveyed on matters concerning their age when they got pregnant, their arrest records, martial stability, and the amount of supervision they gave their children (all of these factors, unsurprisingly, predicting whether or not people continued on in the study for its full duration).

In total, of the 512 eventual cases of reported child maltreatment, only 172 remained in the sample at the 21-year follow up. As one might expect, maternal factors like her education status, arrest record, economic status, and unstable marriages all predicted increased likelihood of eventual child maltreatment. Further, of the 3800 participants, only 161 of them met the criteria for delinquency at 21 years. All of the previous maternal factors predicted delinquency as well: mothers who were arrested, got pregnant earlier, had unstable marriages, less education, and less money tended to produce more delinquent offspring. Adjusting for the maternal factors, however, it was reported that childhood maltreatment still predicted delinquency, but only for the male children. Specifically, maltreatment in males was associated with approximately 2-to-3.5 times as much delinquency as the non-maltreated males. For female offspring, there didn’t seem to be any notable correlation.

Now, as I mentioned, there are some genetic confounds here. It seems probable that parents who maltreat their children are, in some very real sense, different than parents who do not, and those tendencies can be inherited. This also doesn’t necessarily point a causal finger directly at parents, as it is also likely that maltreatment correlates with other social factors, like the peer group a child is liable to have or the neighborhoods they grow up in. The authors also mention that it is possible their measures of delinquency might not capture whatever effects childhood maltreatment (or its correlates) have on females, and that’s the point I wanted to wrap up discussing. To really put these findings on context, we would need to understand what adaptive role these delinquent behaviors – or rather the psychological mechanisms underlying them – have. For instance, frequent recreational drug use and problems fulfilling financial obligations might both signal that the person in question favors short-term rewards over long-term ones; frequent trouble with the law or destroying other people’s property could signal something about how the individual in question competes for social status. Maltreatment does seem to predict (even if it might not cause) different developmental courses, perhaps reflecting an active adjustment of development to deal with local environmental demands.

 The kids at school will all think you’re such a badass for this one

As we reviewed in the initial example, however, the same strategies will not always work equally well for every person. Those who are physically weaker are less likely to successfully enact aggressive strategies, all else being equal, for reasons which should be clear. Accordingly, we might expect that men and women show different patterns of delinquency to the extent they face unique adaptive problems. For instance, we might expect that females who find themselves in particularly hostile environments preferentially seek out male partners capable of enacting and defending against such aggression, as males tend to be more physically formidable (which is not to say that the women themselves might not be more physically aggressive as well). Any hypothetical shifts in mating preferences like these would not be captured by the present research particularly well, but it is nice to see the authors are at least thinking about what sex differences in patterns of delinquency might exist. It would be preferable if they were asking about those differences using this kind of a functional framework from the beginning, as that’s likely to yield more profitable insights and refine what questions get asked, but it’s good to see this kind of work all the same.

References: Abajobir, A., Kisely, S., Williams, G., Strathearnd, L., Clavarino, A., & Najman, J. (2016). Gender differences in delinquency at 21 years following childhood maltreatment: A birth cohort study. Personality & Individual Differences, 106, 95-103. 

Harris, J. (2009). The Nurture Assumption: Why Children Turn Out the Way They Do. Free Press.

Spinning Sexism Research On Accuracy

When it comes to research on sexism, there appear to be many parties interested in the notion that sexism ought to be reduced. This is a laudable goal, and one that I would support; I am very much in favor in treating people as individuals rather than representatives of their race, sex, or any other demographic characteristics. It is unfortunately, however, that this goal often gets side-tracked by an entirely different one: trying to get people to reduce the extent to which people view men and women as different. What I mean by this is that I have seen many attempts to combat sexism by trying to reduce the perception that men and women differ in terms of their psychology, personality, intelligence, and so on; it’s much more seldom that those same voices appear to convince people who inaccurately perceive sex differences as unusually small to adjust their estimate upwards. In other words, rather that championing accuracy is perceptions, there appears to be a more targeted effort for minimizing particular differences; while those are sometimes the same thing (sometimes people are wrong because they overestimate), they are often not (sometimes people are wrong because they underestimate), and when those goals do overlap, the minimization side tends to win out.

Just toss your perceptions in with the rest of the laundry; they’ll shrink

In my last post, I discussed some research by Zell et al (2016) primarily in the service of examining measures of sexism and the interpretation of the data they produce (which I recommend reading first). Today I wanted to give that paper a more in-depth look to illustrate this (perhaps unconscious) goal of trying to get people to view the sexes as more similar than they actually are. Zell et al (2016) begin their introduction by suggesting that most psychological differences between men and women are small, and the cases in which medium to large differences exist – like mating preferences and aggression – tend to be rare. David Schmitt has already put remarks like that into some context, and I highly recommend you read his post on the subject. In the event you can’t be bothered to do so at the moment, one of the most important takeaway points from his post is that even if the differences in any one domain tend to be small on average, when considered across all those domains simultaneously, those small differences can aggregate into much larger ones.

Moreover, the significance of a gender difference is not necessarily determined by its absolute size, either. This was a point Steven Pinker mentioned in a somewhat-recent debate with Elizabeth Spelke (and was touched on again in a recent talk by Jon Haidt at SUNY New Paltz). To summarize this point briefly, if you’re looking at a trait in two normally-distributed populations that are, on average, quite similar, the further from that average value you get, the most extreme the difference between populations become. Pinker makes the point clear in this example:

“…it’s obvious that distributions of height for men and women overlap: it’s not the case that all men are taller than all women. But while at five foot ten there are thirty men for every woman, at six feet there are two thousand men for every woman. Now, sex differences in cognition tend not to be so extreme, but the statistical phenomenon is the same.”

Not only are small sex differences sometimes important, then, (such as when you’re trying to hire people for a job who are in the top 1% of distribution for a trait like intelligence, speed, conscientiousness; you name it) but a large number of small effects (as well as some medium and large ones) can all add up to collectively represent some rather large differences (and that assumes you’re accounting for all relevant sex differences; not just a non-representative sample of them). With all this considered, the declaration at the beginning of Zell et al’s paper that most sex differences tend to be small strikes me less as a statement of empirical concern, but rather one that serves to set up the premise for the rest of their project: specifically, the researchers wanted to test whether people’s scores on the ambivalent sexism inventory predicted (a) the extent to which they perceive sex differences as being large and (b) the extent to which they are inaccurate in their perceptions. The prediction in this case was that people who scored high on their ostensible measures of sexism would be more likely to exaggerate sex differences and more likely to be wrong about their size overall (as an aside, I don’t think those sexism questions measure what the authors hope they do; see my last post).

Pictured: Something not even close to what was being assessed in this study

In their first study, Zell et al (2016) asked about 320 participants to estimate how large they think sex differences are between men and women (from 1-99) were for 48 traits and to answer 6 questions intended to measure their hostile and benevolent sexism (as another aside, I have no idea why those 48 traits in particular were selected). These answers were then averaged for each participant to create an overall score for how large they viewed the sex differences to be, and how high they scored on hostile and benevolent sexism. When the relevant factors were plugged into their regression, the results showed that those higher in hostile (ß = .19) and benevolent (ß = .29) sexism tended to perceive sex differences as larger, on average. When examined by gender, it was found that women (ß = .41) who were higher in benevolent sexism were more likely to perceive sex differences as large (but this was not true for men: ß = .11) and – though it was not significant – the reverse pattern held for hostile sexism, such that women high in hostile sexism were nominally less likely to perceive sex differences as large (ß = -.32).

The more interesting finding, at least as far as I’m concerned, is that in spite of those scoring higher on their sexism scores perceiving sex differences to be larger, they were not really more likely to be wrong about them. Specifically, those who scored higher on benevolent sexism were slightly less accurate (ß = -.20), just as women tended to be less accurate than men (ß = -.19); however, hostile sexism scores were unrelated to accuracy altogether (ß = .003), and no interactions with gender and sexism emerged. To put that in terms of the simple correlations, hostile and benevolent sexism correlated much better with the perceived size of sex differences (rs = .26 and .43, respectively) than they did with accuracy (rs = -.12 and -.22, with the former not being significant and the latter being rather small). Now since we’re dealing with two genders, two sexism scales, and relatively small effects, it is possible that some of these findings are a bit more likely to be statistical flukes; that does tend to happen as you keep slicing data up. Nevertheless, these results are discussed repeated within the context of their paper as representing exaggerations: those scoring higher on these sexism measures are said to exaggerate sex differences, which is odd on account of them not consistently getting them all that wrong.

This interpretation extends to their second study as well. In that experiment, about 230 participants were presented with two mock abstracts and told that only one of them represented an accurate summary of psychological research on sex differences. The accurate version, of course, was the one that said sex differences were small on average and therefore concluded that men and women are very similar to each other, whereas the bogus abstract concluded that gender differences are often large and therefore men and women are very different from one another. As I reviewed in the beginning of the post, small differences can often have meaningful impacts both individually and collectively, so the lines about how men and women are very similar to each other might not reflect an entirely accurate reading of the literature even if the part about small average sex differences did. This setup is already conflating the two statements (“average effect sizes on all these traits is small” and “men and women are very similar across the board”).

“Most of the components aren’t that different from modern cars, so they’re basically the same”

As before, those higher in hostile and benevolent sexism tended to say that the larger sex difference abstract more closely reflected their personal views (women tended to select the large-difference abstract 50.4% of the time compared to men’s 44.2% as well). Now because the authors view the large sex difference abstract as being the fabricated one, they conclude that those higher in those sexism measures are less accurate and more likely to exaggerate these views (they also make a remark that their sexism measures indicate which people “endorse sexist ideologies”; a determination it’s not at all cut out for making). In other words, the authors interpret this finding as those selecting the large-differences abstract to hold “empirically unsupported” views (which in a sort-of ironic sense means that, as the late George Carlin put it, “Men are better at it” when it comes to recognizing sex differences).

This is an interesting methodological trick they employ: since they failed to find much in the way of a correlation between sexism scores and accuracy in their first study (it existed sometimes, but was quite small across the board and certainly much smaller than the perception of size correlation), they created a coarser and altogether worse measure of accuracy in the second study and use that to support their views that believing men and women tend to be rather different is wrong instead. As the old saying goes, if at first you don’t succeed, change your measures until you do.

References: Zell, E., Strickhouser, J., Lane, T., & Teeter, S. (2016). Mars, Venus, or Earth? Sexism and the exaggeration of psychological gender differences. Sex Roles, 75, 287-300.

Research Tip: Ask About What You Want To Measure

Recently I served as a reviewer for a research article that had been submitted to a journal for publication. Without going into too much detail as to why, the authors of this paper wanted to control for people’s attitudes towards casual sex when conducting their analysis. They thought that it was possible people who were more sexually-permissive when it comes to infidelity might respond to certain scenarios differently than those who were less sexually-permissive. If you were the sensible type of researcher, you might do something like ask your participants to indicate on some scale as to how acceptable or unacceptable they think sexually infidelity is, then. The authors of this particular paper opted for a different, altogether stranger route: they noted that people’s attitudes towards infidelity correlate (imperfectly) with their political ideology (i.e., whether they consider themselves to be liberals or conservatives). So, rather than ask participants directly about how acceptable infidelity is (what they actually wanted to know), they asked participants about their political ideology and used that as a control instead.

 ”People who exercise get tired, so we measured how much people napped to assess physical fitness”

This example is by no means unique; psychology researchers frequently try to ask questions about topic X in the hopes of understanding something about topic Y. This can be acceptable at times, specifically when topic Y is unusually difficult – but not impossible – to study directly. After all, if topic Y is impossible to directly study, then one obviously cannot say that studying topic X tells you something about Y with much confidence, as you would have no way of assessing the relationship between X and Y to begin with. Assuming that the relationship between X and Y has been established and it is sufficiently strong and Y is unusually difficult to study directly, then there’s a good, practical case to be made for using X instead. When that is done, however, it should always be remembered that you aren’t actually studying what you’d like to study, so it’s important to not get carried away with the interpretation of your results.

This brings us nicely to the topic of research on sexism. When people hear the word “sexism” a couple things come to mind: someone who believes one sex is (or should be) – socially, morally, legally, psychologically, etc – inferior to the other, or worth less; someone who wouldn’t want to hire a member of one sex for a job (or intentionally pays them less if they did) strictly because of that variable regardless of their qualifications; someone who inherently dislikes members of one sex. While this list is by no means exhaustive, I suspect things like these are probably the prototypical examples of sexism; some kind of explicit, negative attitude about people because of their sex per se that directly translates into behavior. Despite this, people who research sexism don’t usually ask about such matters directly, as far as I’ve seen. To be clear, they easily could ask such questions assessing such attitudes in straightforward manners (in fact, they used to do just that with measures like the “Attitudes Towards Women Scale” in the 1970s), but they do not. As I understand it, the justification for not asking about such matters directly is because it has become more difficult to find people who actually express such views (Loo & Thorpe, 1998). As attitudes had already become markedly less sexist from 1972 to 1998, one can only guess at how much more change occurred from then to now. In short, it’s becoming rare to find blatant sexists anymore, especially if you’re asking college students.

Many researchers interpret that difficulty as being the result of people still holding sexist attitudes but either (a) are not willing express them publicly for fear of condemnation, or (b) are not consciously aware that they hold such views. As such, researchers like to ask about questions about “Modern Sexism” or “Ambivalent Sexism“; they maintain the word “sexism” in their scales, but they begin to ask about things which are not what people first think of when they hear the term. They no longer ask about explicitly sexist attitudes. Therein lies something of a problem, though: if what you really want to know is whether people hold particular sexist beliefs or attitudes, you need some way of assessing those attitudes directly in order to determine that other questions which don’t directly ask about that sexism will accurately reflect it. However, if such a method of assessing those beliefs accurately, directly, and easily does exist, then it seems altogether preferable to use that method instead. In short, just ask about the things you want to ask about. 

“We wanted to measure sugar content, so we assessed how much fruit the recipe called for”

If you continue on with using an alternate measure – like using the Ambivalent Sexism Inventory (ASI), rather than the Attitudes towards Women Scale – then you really should restrict your interpretations to things you’re actually asking about. As a quick example, let’s consider the ASI, which is made up of a hostile and benevolent sexism component. Zell et al (2016) summarize the scale as follows:

“Hostile sexism is an adversarial view of gender relations in which women are perceived as seeking control over men. Benevolent sexism is a subjectively positive view of gender relations in which women are perceived as pure creatures who ought to be protected, supported, and adored; as necessary companions to make a man complete; but as weak and therefore best relegated to traditional gender roles (e.g., homemaker).”

In other words, the benevolent scale measures the extent to which women are viewed as children: incapable of making their own decisions and, as such, in need of protection and provisioning by men. The hostile scale measures the extent to which men don’t trust women and view them as enemies. Glick & Fiske (1996) claim that  ”...hostile and benevolent sexism…combine notions of the exploited group’s lack of competence to exercise structural power with self-serving “benevolent” justifications.” However, not a single measure on either the hostile or benevolent sexism inventory actually asks about female competencies or whether women ought to be restricted socially. 

To make this explicit, let’s consider the questions Zell et al (2016) used to assess both components. In terms of hostile sexism, participants were asked to indicate their agreement with the following three statements:

  • Women seek power by gaining control over men
  • Women seek special favors under the guise of equality
  • Women exaggerate their problems at work

There are a few points to make about these questions: first, they are all clearly true to some extent. I say that because these are behaviors that all kinds of people engage in. If these behaviors are not specific to one sex – if both men and women exaggerate their problems at work – then agreement with the idea that women do does not stop me from believing men do this as well and, accordingly, does not necessarily track any kind of sexist belief (the alternative, I suppose, is to believe that women never exaggerate problems, which seems unlikely). If the questions are meant to be interpreted as a relative statement (e.g., “women exaggerate their problems at work more than men do”), then that statement needs to first be assessed empirically as true or false before you can say that endorsement of it represents sexism. If women actually do tend to exaggerate problems at work more (a matter that is quite difficult to objectively determine because of what the term exaggerate means), then agreement with the statement just means you accurately perceive reality; not that you’re a sexist.

More to the point, however, none of the measures ask about what the researchers interpret them to mean: women seeking special favors does not imply they are incompetent or unfit to hold positions outside of the home, nor does it imply that one views gender relations primarily as adversarial. If those views are really what a researcher is trying to get at, then they ought to just ask about them directly. A similar story emerges for the benevolent questions:

  • Women have a quality of purity few men possess
  • Men should sacrifice to provide for women
  • Despite accomplishment, men are incomplete without women

 Again, I see no mention of women’s competency, ability, intelligence, or someone’s endorsement of strict gender roles. Saying that men ought to behave altruistically towards women in no way implies that women can’t manage without men’s help. When a man offers to pay for an anniversary dinner (a behavior which I have seen labeled sexist before), he is usually not doing so because he feels his partner is incapable of paying anymore than my helping a friend move suggests I view them as a helpless child. 

“Our saving you from this fire implies you’re unfit to hold public office”

The argument can, of course, be made that scores on the ASI are related to the things these researchers actually want to measure. Indeed, Glick & Fiske (1996) made that very argument: they report that the hostile sexism scores (controlling for the benevolent scores) did correlate with “Old Fashion Sexism” and “Attitudes towards Women” scores (rs = .43 and .60, respectively, bearing in mind that was almost 20 years ago and these attitudes are changing). However, the correlations between benevolent sexism scores and these sexist attitudes were effectively zero (rs = -.03 and .04, respectively). In other words, it appears that people endorse these statements for reasons that have nothing at all to do with whether they view women as weak, or stupid, or any other pejorative you might throw out there, and their responses may tell you nothing at all about their opinion concerning gender roles. If you want to know about those matters, then ask about them. In general, it’s fine to speculate about what your results might mean – how they can best be interpreted – but an altogether easier path is to simply ask about such matters directly and reduce the need for pointless speculation.

 References: Glick, P. & Fiske, S. (1996). The ambivalent sexism inventory: Differentiating hostile and benevolent sexism. Journal of Personality & Social Psychology, 70, 491-512.

Loo, R. & Thorpe, K. (1998). Attitudes towards women’s roles in society: A replication after 20 years. Sex Roles, 39, 903-912.

Zell, E., Strickhouser, J., Lane, T., & Teeter, S. (2016). Mars, Venus, or Earth? Sexism and the exaggeration of psychological gender differences. Sex Roles, 75, 287-300.

Money For Nothing, But The Chicks Aren’t Free

When people see young, attractive women in relationships with older and/or unattractive men, the usual perception that comes to mind is that the relationship revolves around money. This perception is usual because it tends to be accurate: women do, in fact, tend to prefer men who both have access to financial resources and who are willing to share them.  What is rather notable is that the reverse isn’t quite as a common: a young, attractive man shacking up with an older, rich woman just doesn’t call too many examples to mind. Women seem to have a much more pronounced preference for men with wealth than men have for women. While examples of such preferences playing themselves out in real life exist anecdotally, it’s always good to try and showcase their existence empirically.

Early attempts were made by Dr. West, but replications are required

This brings me to a new paper by Arnocky et al (2016) that examined how altruism affects mating success in humans (as this is still psychology research, “humans” translates roughly as “undergraduate psychology majors”, but such is the nature of convenience samples). The researchers first sought (a) to document that more altruistic people really were preferred as mating partners (spoilers: they are), and then (b) to try and explain why we might expect them to be. Let’s begin with what they found, as that much is fairly straightforward. In their first study, Arnocky et al (2016) recruited 192 women and 105 men from a Canadian university and asked them to complete a few self-report measures: an altruism scale (used to measure general dispositions towards providing aid to others when reciprocation is unlikely), a mating success scale (measuring perceptions of how desirable one tends to be towards the opposite sex), their numbers of lifetime sexual partners, as well as the number of those that were short-term, the number of times over the last month they had sex with their current partner (if they had one, which about 40% did), and a measure of their personality more generally.

These measures were then entered into a regression (controlling for personality). When it came to predicting perceived mating success, reported altruism was a significant predictor (ß = 0.25), but neither sex nor the altruism-sex interaction was. This suggests that both men and women tend become more attractive to the opposite sex if they behave more altruistically (or, conversely, that people who are more selfish are less desirable, which sounds quite plausible). However, what it means for one to be successful in the mating domain varies by sex: for men, having more sexual partners usually implies a greater level of success, whereas the same does not hold true for women as often (as gametes are easy to obtain for women, but investment is difficult). In accordance with this point, it was also found that altruism predicted the number of lifetime sexual partners overall (ß = .16), but this effect was specific to men: more altruistic men had more sexual partners (and more casual ones), whereas more altruistic women did not. Finally, within the contexts of existing relationships, altruism also (sort of) predicted the number of times someone had sex with their partner in the last month (ß = .27); while there was not a significant interaction with sex, a visual inspection of the provided graphs suggest that if this effect existed, it was being predominately carried by altruistic women having more sex within a relationship; not the men.

Now that’s all well and good, but the authors wanted to go a little further. In their second study, rather than just asking participants about how altruistic they were, they offered participants the opportunity to be altruistic: after completing the survey, participants could indicate how much (if any) of their earnings they wanted to donate to a charity of their choice. That way, you get what might be a less-biased measure of one’s actual altruism (rather than their own perception of it). Another 335 women and 189 men were recruited for this second phase and, broadly, the results follow the same general pattern, but there were some notable differences. In terms of mating success, actual altruistic donations (categorized as either making a donation or not, rather than the amount donated) were not a good predictor (ß = -.07). In terms of number of lifetime dating and sexual partners, however, the donation-by-sex interaction was significant, indicating that more charitable men – but not women – had a greater number of relationships and sexual partners (perhaps suggesting that charitable men tend to have more, but shorter, relationships, which isn’t necessarily a good thing for the women involved). Donations also failed to predict the amount of sex participants had been having in their relationship in the last month.

Guess the blood drive just isn’t a huge turn on after all

With these results in mind, there are two main points I wanted to draw attention to. The first of these concerns the measures of altruism in general: effectively charitable behaviors to strangers. While such a behavior might be a more “pure” form of altruistic tendencies as compared with, say, helping a friend move or giving money to your child, it does pose some complications for the present topic. Specifically, when looking for a desirable mate, people might not want someone who is just generally altruistic. After all, it doesn’t always do me much good if my committed partner is spending time and investing resources in other people. I would probably prefer that resources be preferentially directed at me and those I care about, rather than strangers, and I might especially dislike it if altruism directed towards strangers came at my expense (as the same resources can’t be invested in me and someone else most of the time). While it is possible that such investments in strangers could return to me later in the form of them reciprocating such aid to my partner, it seems unlikely that deficit would be entirely and consistently made up, let alone surpassed.

To make the point concrete, if someone was equally altruistic towards all people, there would be little point in forming as kind of special relationship with that kind person (friendships or otherwise) because you’d get the same benefits from them regardless of how much you invested in them (even if that amount was nothing).

This brings me to the second point I wanted to discuss: the matter of why people like the company of altruists. There are two explanations that come to mind. The first explanation is simple: people like access to resources, and altruists tend to provide them. This explanation should hardly require much in the way of testing given its truth is plainly obvious. The second explanation is more complex, and it’s one the authors favor: altruism honestly signals some positive, yet difficult-to-observe quality about the altruist. For instance, if I were to donate blood, or my time to clean up a park, this would tell you something about my underlying genetic qualities, as an individual in worse condition couldn’t shoulder the costs of altruism effectively. In this sense, altruism functions in a comparable manner to a peacock’s tail feathers; it’s a biologically-honest signal because it’s costly.

While it does have some plausibility, this signaling explanation runs into some complications. First, as the authors note, women donated more than men did (70% to 57%), despite donating predicting sexual behavior better for men. If women were donating to signal some positive qualities in the mating domain, it’s not at all clear it was working. Further, patterns of charitable donations in the US show a U-shaped distribution, whereby those with access to the most and  the fewest financial resources tend to donate more than those in the middle. This seems like a pattern the signaling explanation should not predict if altruism is meaningfully and consistently tied to important, but difficult-to-observe biological characteristics. Finally, while the argument could be made that altruism directed towards friends, sexual partners, and kin are not necessarily indicative of someone’s willingness to donate to strangers (i.e., how altruistic they are dispositionally might not predict how nepotistic they are), well, that’s kind of a problem for the altruism-as-signaling model. If donations towards strangers are fairly unpredictive of altruism towards closer relations, then they don’t really tell you what you want to know.  Specifically, if you want to know how good of a friend or dating partner someone would be for you, a better cue is how much altruism they direct towards their friends and romantic partners; not how much they direct to strangers.

“My boyfriend is so altruistic, buying drinks for other women like that”

Last, we can consider the matter of why people behave altruistically, with respect to the mating domain. (Very) broadly speaking, there are two primary challenges people need to overcome: attracting a mate and retaining them. Matters get tricky here, as altruism can be used for both of these tasks. As such, a man who is generally altruistic towards lot of people might be using altruism as a means of attracting the attention of prospective mates without necessarily intending to keep them around. Indeed, the previous point about how altruistic men report having more relationships and sexual partners could be interpreted in just such a light. There are other explanations, of course, such as the prospect that generally selfish people simply don’t have many relationships at all, but these need to be separated out. In either case, in terms of how much altruism we provide to others, I suspect that the amount provided to strangers and charitable organizations only makes up a small fraction; we give much more towards friends, family, and lovers regularly. If that’s the case, measuring someone’s willingness to donate in those fairly uncommon contexts might not capture their desirability as partner as well as we would like.

References: Arnocky, S., Piche, T., Albert, G., Ouellette, D., & Barclay, P. (2016). Altruism predicts mating success in humans. British Journal of Psychology, DOI:10.1111/bjop.12208

 

Skepticism Surrounding Sex

It’s a basic truth of the human condition that everybody lies; the only variable is about what

One of my favorite shows from years ago was House; a show centered around a brilliant but troubled doctor who frequently discovers the causes of his patient’s ailments through discerning what they – or others – are lying about. This outlook on people appears to be correct, at least in spirit. Because it is sometimes beneficial for us that other people are made to believe things that are false, communication is often less than honest. This dishonesty entails things like outright lies, lies by omission, or stretching the truth in various directions and placing it in different lights. Of course, people don’t just lie because deceiving others is usually beneficial. Deception – much like honesty – is only adaptive to the extent that people do reproductively-relevant things with it. Convincing your spouse that you had an affair when you didn’t is dishonest for sure, but probably not a very useful thing to do; deceiving someone about what you had for breakfast is probably fairly neutral (minus the costs you might incur from coming to be known as a liar). As such, we wouldn’t expect selection to have shaped our psychology to lie about all topics with equal frequency. Instead, we should expect that people tend to preferentially lie about particular topics in predictable ways.

Lies like, “This college degree will open so many doors for you in life”

The corollary idea to that point concerns skepticism. Distrusting the honesty of communications can protect against harmful deceptions, but it also runs the risk of failing to act on accurate and beneficial information. There are costs and benefits to skepticism as there are to deception. Just as we shouldn’t expect people to be dishonest about all topics equally often, then, we shouldn’t expect people to be equally skeptical of all the information they receive either. This is point I’ve talked about before with regards to our reasoning abilities, whereby information agreeable to our particular interests tends to be accepted less critically, while disagreeable information is scrutinized much more intensely.

This line of thought was recently applied to the mating domain in a paper by Walsh, Millar, & Westfall (2016). Humans face a number of challenges when it comes to attracting sexual partners typically centered around obtaining the highest quality of partner(s) one can (metaphorically) afford, relative to what one offers to others. What determines the quality of partners, however, is frequently context specific: what makes a good short-term partner might differ from what makes a good long-term partner and – critically, as far as the current research is concerned – the traits that make good male partners for women are not the same as those that make good females partner for men. Because women and men face some different adaptive challenges when it comes to mating, we should expect that they would also preferentially lie (or exaggerate) to the opposite sex about those traits that the other sex values the most. In turn, we should also expect that each sex is skeptical of different claims, as this skepticism should reflect the costs associated with making poor reproductive decisions on the basis of bad information.

In case that sounds too abstract, consider a simple example: women face a greater obligate cost when it comes to pregnancy than men do. As far as men are concerned, their role in reproduction could end at ejaculation (which it does, for many species). By contrast, women would be burdened with months of gestation (during which they cannot get pregnant again), as well as years of breastfeeding prior to modern advancements (during which they also usually can’t get pregnant). Each child could take years of a woman’s already limited reproductive lifespan, whereas the man has lost a few minutes. In order to ease those burdens, women often seek male partners who will stick around and invest in them and their children. Men who are willing to invest in children should thus prove to be more attractive long-term partners for women than those who are unwilling. However, a man’s willingness to stick around needs to be assessed by a woman in advance of knowing what his behavior will actually be. This might lead to men exaggerating or lie about their willingness to invest, so as to encourage women to mate with them. Women, in turn, should be preferentially skeptical of such claims, as being wrong about a man’s willingness to invest is costly indeed. The situation should be reversed for traits that men value in their partners more than women.

Figure 1: What men most often value in a woman

Three such traits for both men and women were examined by Walsh et al (2016). In their study, eight scenarios depicting a hypothetical email exchange between a man and woman who had never met were displayed to approximately 230 (mostly female; 165) heterosexual undergraduate students. For the women, these emails depicted a man messaging a woman; for men, it was a woman messaging a man. The purpose of these emails was described as the person sending them looking to begin a long-term intimate relationship with the recipient. Each of these emails described various facets of the sender, which could be broadly classified as either relevant primarily to female mating interests, relevant to male interests, or neutral. In terms of female interests, the sender described their luxurious lifestyle (cuing wealth), their desire to settle down (commitment), or how much they enjoy interacting with children (child investment). In terms of male interests, the sender talked about having a toned body (cuing physical attractiveness), their openness sexually (availability/receptivity), or their youth (fertility and mate value). In the two neutral scenarios, the sender either described their interest in stargazing or board games.

Finally, the participants were asked to rate (on a 1-5 scale) how deceitful they thought the sender was, whether they believed the sender or not, and how skeptical they were of the claims in the message. These three scores were summed for each participant to create a composite score of believability for each of the messages (the lower the score, the less believable it was rated as being). Those scores were then averaged across the female-relevant items (wealth, commitment, and childcare), the male-relevant items (attractiveness, youth, and availability), and the control conditions. (Participants also answered questions about whether the recipient should respond and how much they personally liked the sender. No statistical analyses are reported on those measures, however, so I’m going to assume nothing of note turned up)

The results showed that, as expected, the control items were believed more readily (M = 11.20) than the male (M = 9.85) or female (9.6) relevant items. This makes sense, inasmuch as believing lies about stargazing or interests in board games aren’t particularly costly for either sex in most cases, so there’s little reason to lie about them (and thus little reason to doubt them); by contrast, messages about one’s desirability as a partner have real payoffs, and so are treated more cautiously. However, an important interaction with the sex of the participant was uncovered as well: female participants were more skeptical on the female-relevant items (M = about 9.2) than males were (M = 10.6); similarly, males were more likely to be skeptical in male-relevant conditions  (M = 9.5) than females were (M = 10). Further, the scores for the individual items all showed evidence of the same sex kinds of differences in skepticism. No sex difference emerged for the control condition, also as expected.

In sum, then – while these differences were relatively small in magnitude – men tended to be more skeptical of claims that, if falsely believed, were costlier for them than women, and women tended to be more skeptical of claims that, if falsely believed, were costlier for them than men. This is a similar pattern to that found in the reasoning domain, where evidence that agrees with one’s position is accepted more readily than evidence that disagrees with it.

“How could it possibly be true if it disagrees with my opinion?”

The authors make a very interesting point towards the end of their paper about how their results could be viewed as inconsistent with the hypothesis that men have a bias to over-perceived women’s sexual interest. After all, if men are over-perceiving such interest in the first place, why would they be skeptical about claims of sexual receptivity? It is possible, of course, that men tend to over-perceive such availability in general and are also skeptical of claims about its degree (e.g., they could still be manipulated by signals intentionally sent by females and so are skeptical, but still over-perceive ambiguous or less-overt cues), but another explanation jumps out at me that is consistent with the theme of this research: perhaps when asked to self-report about their own sexual interest, women aren’t being entirely accurate (consciously or otherwise). This explanation would fit well with the fact that men and women tend to perceive a similar level of sexual interest in other women. Then again, perhaps I only see that evidence as consistent because I don’t think men, as a group, should be expected to have such a bias, and that’s biasing my skepticism in turn.

References: Walsh, M., Millar, M., & Westfall, S. (2016). The effects of gender and cost on suspicion in initial courtship communications. Evolutionary Psychological Science, DOI 10.1007/s40806-016-0062-8

Why Women Are More Depressed Than Men

Women are more likely to be depressed than men; about twice as likely here in the US, as I have been told. It’s an interesting finding, to be sure, and making sense of it poses a fun little mystery (as making sense of many things tends to). We don’t just want to know that women are more depressed than men; we also want to know why women are more depressed. So what are the causes of this difference? The Mayo Clinic floats a few explanations, noting that this sex difference appears to emerge around puberty. As such, many of the explanations they put forth center around the problems that women (but not men) might face when undergoing that transitional period in their life. These include things like increased pressure to achieve in school, conflict with parents, gender confusion, PMS, and pregnancy-related factors. They also include ever-popular suggestions such as societal biases that harm women. Now I suspect these are quite consistent with the answers you would get if queried your average Joe or Jane on the street as to why they think women are more depressed. People recognize that depression often appears to follow negative life events and stressors, and so they look for proximate conditions that they believe (accurately or not) disproportionately affect women.

Boys don’t have to figure out how to use tampons; therefore less depression

While that seems to be a reasonable strategy, it produces results that aren’t entirely satisfying. First, it seems unlikely that women face that much more stress and negative life events than men do (twice as much?) and, secondly, it doesn’t do much to help us understand individual variation. Lots of people face negative life events, but lots of them also don’t end up spiraling into depression. As I noted above, our understanding of the facts related to depression can be bolstered by answering the why questions. In this case, the focus many people have is on answering the proximate whys rather than the ultimate ones. Specifically, we want to know why people respond to these negative life events with depression in the first place; what adaptive function depression might have. Though depression reactions appear completely normal to most, perhaps owing to their regularity, we need to make that normality strange. If, for example, you imagine a new mouse mother facing the stresses of caring for her young in a hostile world, a postpartum depression on her part might seem counterproductive: faced with the challenges of surviving and caring for her offspring, what adaptive value would depressive symptoms have? How would low energy, a lack of interest in important everyday activities, and perhaps even suicidal ideation help make her situation better? If anything, they would seem to disincline her from taking care of these important tasks, leaving her and her dependent offspring worse off. This strangeness, of course, wouldn’t just exist in mice; it should be just as strange when we see it in humans.

The most compelling adaptive account of depression I’ve read (Hagen, 2003) suggests that the ultimate why of depression focuses on social bargaining. I’ve written about it before, but the gist of the idea is as follows: if I’m facing adversity that I am unlikely to be able to solve alone, one strategy for overcoming that problem is to recruit others in the world to help me. However, those other people aren’t always forthcoming with the investment I desire. If others aren’t responding to my needs adequately, it would behoove me to try and alter their behavior so as to encourage them to increase their investment in me. Depression, in this view, is adapted to do just that. The psychological mechanisms governing depression work to, essentially, place the depressed individual on a social strike. When workers are unable to effectively encourage an increased investment from their employers (perhaps in the form of pay or benefits), they will occasionally refuse to work at all until their conditions improve. While this is indeed costly for the workers, it is also costly for the employer, and it might be beneficial for the employer to cave to the demands rather than continue to face the costs of not having people work. Depression shows a number of parallels to this kind of behavior, where people withdraw from the social world – taking with them the benefits they provided to others – until other people increase their investment in the depressed individual to help see them through a tough period.

Going on strike (or, more generally, withdrawing from cooperative relationships), of course, is only one means of getting other people to increase their investment in you; another potential strategy is violence. If someone is enacting behaviors that show they don’t value me enough, I might respond with aggressive behaviors to get them to alter that valuation. Two classic examples of this could be shooting someone in self-defense or a loan-shark breaking a delinquent client’s legs. Indeed, this is precisely the type of function that Sell et al (2009) proposed that anger has: if others aren’t giving me my due, anger motivates me to take actions that could recalibrate their concern for my welfare. This leaves us with two strategies – depression and anger – that can both solve the same type of problem. The question arises, then, as to which strategy will be the most effective for a given individual and their particular circumstances. This raises a rather interesting possibility: it is possible that the sex difference in depression exists because the anger strategy is more effective for men, whereas the depression strategy is more effective for women (rather than, say, because women face more adversity than men). This would be consistent with the sex difference in depression arising around puberty as well, since this is when sex differences in strength also begin to emerge. In other words, both men and women have to solve similar social problems; they just go about it in different ways. 

“An answer that doesn’t depend on wide-spread sexism? How boring…”

Crucially, this explanation should also be able to account for within-sex differences as well: while men are more able to successfully enact physical aggression than women, not all men will be successful in that regard since not all men possess the necessary formidability. The male who is 5’5″ and 130 pounds soaking wet likely won’t win against his taller, heavier, and stronger counterparts in a fight. As such, men who are relatively weak might preferentially make use of the depression strategy, since picking fights they probably won’t win is a bad idea, while those who are on the stronger side might instead make use of anger more readily. Thankfully, a new paper by Hagen & Rosenstrom (2016) examines this very issue; at least part of it. The researchers sought to test whether upper-body strength would negatively predict depression scores, controlling for a number of other, related variables.

To do so, they accessed data from the National Health and Nutrition Examination Survey (NHANES), netting a little over 4,000 subjects ranging in age from 18-60. As a proxy for upper-body strength, the authors made use of the measures subjects had provided of their hand-grip strength. The participants had also filled out questions concerning their depression, height and weight, socioeconomic status, white blood cell count (to proxy health), and physical disabilities. The researchers predicted that: (1) depression should negatively correlate with grip-strength, controlling for age and sex, (2) that relationship should be stronger for men than women, and (3) that the relationship would persist after controlling for physical health. About 9% of the sample qualified as depressed and, as expected, women were more likely to report depression than men by about 1.7 times. Sex, on its own, was a good predictor of depression (in their regression, ß = 0.74).

When grip-strength was added into the statistical model, however, the effect of sex dropped into the non-significant range (ß = 0.03), while strength possessed good predictive value (ß = -1.04). In support of the first hypothesis, then, increased upper-body strength did indeed negatively correlate with depression scores, removing the effect of sex almost entirely. In fact, once grip strength was controlled for, men were actually slightly more likely to report depression than women (though this didn’t appear to be significant). Prediction 2 was not supported, however, with their being no significant interaction between sex and grip-strength on measures of depression. This effect persisted even when controlling for socioeconomic status, age, anthropomorphic, and hormonal variables. However, physical disability did attenuate the relationship between strength and depression quite a bit, which is understandable in light of the fact that physically-disabled individuals likely have their formidability compromised, even if they have stronger upper bodies (an example being a man in a wheelchair having good grip strength, but still not being much use in a fight). It is worth mentioning that the relationship between strength and depression appeared to grow larger over time; the authors suggest this might have something to do with older individuals having more opportunities to test their strength against others, which sounds plausible enough. 

Also worth noting is that when depression scores were replaced with suicidal ideation, the predicted sex-by-strength interaction did emerge, such that men with greater strength reported being less suicidal, while women with greater strength reported being more suicidal (the latter portion of which is curious and not predicted). Given that men succeed at committing suicide more often than women, this relationship is probably worth further examination.  

“Not today, crippling existential dread”

Taken together with findings from Sell et al (2009) – where men, but not women, who possessed greater strength reported being quicker to anger and more successful in physical conflicts – the emerging picture is one in which women tend to (not consciously) “use” depression as a means social bargaining because it tends to work better for them than anger, whereas the reverse holds true for men. To be clear, both anger and depression are triggered by adversity, but those events interact with an individual’s condition and their social environment in determining the precise response. As the authors note, the picture is likely to be a dynamic one; not one that’s as simple as “more strength = less depression” across the board. Of course, other factors that co-vary with physical strength and health – like attractiveness – could also being playing a roll in the relationship with depression, but since such matters aren’t spoken to directly by the data, the extent and nature of those other factors is speculative.

What I find very persuasive about this adaptive hypothesis, however – in addition to the reported data – is that many existing theories of depression would not make the predictions tested by Hagen & Rosenstrom (2016) in the first place. For example, those who claim something like, “depressed people perceive the world more accurately” would be at a bit of a loss to explain why those who perceive the world more accurately also seem to have lower upper-body strength (they might also want to explain why depressed people don’t perceive the world more accurately, either). A plausible adaptive hypothesis, on the other hand, is useful for guiding our search for, and understanding of, the proximate causes of depression.

References: Hagen, E.H. (2003). The bargaining model of depression. In: Genetic and Cultural Evolution of Cooperation, P. Hammerstein (ed.). MIT Press, 95-123

Hagen, E. & Rosenstrom, T. (2016). Explain the sex difference in depression with a unified bargaining model of anger and depression. Evolution, Medicine, & Public Health, 117-132

Sell, A., Tooby, J., & Cosmides, L. (2009). Formidability and the logic of human anger. Proceedings of the National Academy of Sciences, 106, 15073-78.