Is There Any Good Evidence That Porn Is Harmful To Relationships?

In my last post, I noted briefly how technology has made it easier than ever to access a variety of pornographic images, whether produced personally or professionally. Much like concerns about how violent video games might make people who play them more violent, there have also been concerns raised about how pornography becoming more prevalent might also lead to certain, undesirable outcomes, such as rape as weakened relationships. As for the video game concern, there is some evidence that the aggression (or rather anger) caused by video games might have a lot less to do with violent content per se than it has to do with losing (full disclosure: I have been unable to locate the paper, so I can’t assess the claims made in it personally, but this explanation should be easily and intuitively understandable to anyone who has seriously engaged in competitive play. Gamers don’t rage quit over violent content; they rage quit because they lost). Similarly, there have been many concerns raised about pornography over the years, many of which hinge on the idea that pornography might lead to people (specifically men) to develop negative attitudes towards women and, accordingly, be more likely to rape them or to accept rape more generally.

Tissue companies vigorously denied that such a link existed

As pornography has become more widely available – thanks in no small part to the internet – rates of rape appear to have declining rather markedly over the same time period; in much the same way, violence has been declining despite violent video games being more common and accessible than ever. The world is a complex place and there are plenty of variables at play, so those correlations are just that. Nevertheless, the evidence that pornography causes any kind of sexual offending is “inconsistent at best” (Ferguson & Hartley, 2009) and, given the nature of the topic, one might reasonably suspect that at least some of that inconsistency has to do with researchers setting out to find certain conclusions. To be blunt about it, some researchers probably “have their answer”, so to speak, before they even begin the research, and might either game their projects to find that result, or interpret otherwise ambiguous results in a manner consistent with their favored hypothesis.

On that note, there was a recent post by Peg Streep concerning the negative effects that pornography might have on intimate relationships. In no uncertain terms, Peg suggests that (1) relationships with porn are less stable, (2) watching porn makes people less committed to their relationships, and (3) that it leads to people cheating on their partners. The certainty with which these points were made appears to stand in marked contrast to the methodological strength of studies she mentions, even from her own summaries of them (As an aside, in the comments section Peg also appears to insinuate that video games make people more violent as well; just a fun coincidence). Given that the studies are covered in less-than-adequate detail, I decided it track down the research she presented for myself and see if there was any good evidence that pornography use has a negative and causal relationship with commitment and intimate relationships.

The first study comes from Maddox et al (2011). This paper surveyed the pornography viewing habits of around 1,300 individuals (whether alone, with a partner, or not at all) and examined whether there was any relationship between viewing pornography and various relationship measures. Those who reported not viewing pornography tended to be more religious, tended to escalate fights less (d = 0.26), thought their relationship was going better (d = 0.22), and were more dedicated to their relationships (d = 0.25, approximately). Further, those who watched porn were less likely to report being satisfied sexually in their relationship (d = 0.21) and also appeared to be two- to three-times as likely to report infidelity. However, the authors explicitly acknowledge on more than one occasion that their data is correlational in nature and provided no evidence of causality. Such research might simply suggest those who like pornography are different than those who do not like it, or that “…individuals who are unhappy with their relationships seek out [pornography] on their own as an outlet for sexual energy”. The pornography itself might have very little to do with relationship strength.

It might have plenty to do with arm strength, though

The second paper Peg mentions at least contains an experiment, which should, in principle, be better for determining if there is any causal relationship here. Unfortunately, there exists a gap between principle and practice here. The paper, by Lambert et al (2012) is rather long, so I’m only going to focus on the actual experiment within it and ignore the other correlational work (as those issues would be largely a retread of the last paper). The experiment involved having current porn users to either (a) refrain from using porn or (b) eating their favorite food for three weeks. The participants (N = 20) also maintained a daily dairy of their porn use. Initially, the two groups reported similar porn usage (M = 3.73 and 4.07 viewings per month – I think – respectively) and relationship commitment (estimated 72% and 62% chance of being with their partner in the future, respectively). After the three week period, those who attempted to abstain from porn reported less viewing (M = 1.42) than those in the food-abstaining group (M = 3.88); the former group also reported greater relationship commitment (63% chance of staying together over time) relative to the food-abstainers (30% chance) at the end of the three weeks.

So was porn the culprit here? Well, I think it’s very doubtful. First of all, the sample size of 10 per group is pitifully small and I would not want to draw any major conclusions from that. Second, both groups were initially high on their relationship commitment despite both groups also watching porn. Third, and perhaps most importantly, what this study found was not an increase in commitment when people watched less porn, directly contradicting what Peg says about the results (that group saw a decrease as well, albeit only a 10% drop); it just found a large decrease in the group that continued to do what it had been doing this whole time. In other words, the authors are positing that a constant (porn usage) was responsible for a dramatic and sudden decline, whereas their manipulation (less porn usage) was responsible for things staying (sort of) constant. I find that very unlikely; more likely, I would say, is that one or two couples within the food-abstaining group happened to have hit a rough patch unrelated to the porn issue and, because the sample size was so small, that’s all it took to find the result.

The final paper Peg mentions comes from Gwinn et al (2013), and examined the relationship between porn and cheating. The authors report two studies: in the first, 74 students either wrote about a sexually explicit scene or an action scene from a movie or show they had seen in the last month; they were then asked to think about what options they had for alternative sexual partners. Those who wrote about the sexual scene rated their options as an average 3.3 out of 7, compared with the 2.6 for the action group (Of note: only half the subjects in the sex group wrote about porn; the other half wrote about non-porn sex scenes). Further, those in the sexual group did not report any difference in their current relationship satisfaction than those in the action group. In the second study, 291 students had their porn habits measured at time one and their cheating behavior (though this was not exclusively sexual behavior) measured at time two. They found a rather weak but positive correlation between the two: pornography use at time one could uniquely account for approximately 1% of the variance in cheating 12 weeks later. So, much like the first study, this one tells us nothing about causation and, even if it did, the effect was small enough to be almost zero.

But go ahead; blame porn. I’m sure you will anyway.

So, to summarize: the first study suggests that people who like porn might be different than those who do not, the second study found that watching less porn did not increase commitment (in direct contradiction to what Peg said about it), and the final study found that porn usage explains almost no unique variance in infidelity on its own, nor does it effect relationship satisfaction. So, when Peg suggests that “The following three studies reveal that it has a greater effect on relationships than those we usually discuss” and, ”Pornography is not as benign as you think, especially when it comes to romantic relationships“, and, “The fantasy alternative leads to real world cheating“, she doesn’t seem to have an empirical leg to stand on. Similarly, in the comments, when she writes “Who blamed cheating on porn? Neither the research nor I. The research indicates the watching porn elevates the odds of cheating for the reasons noted” (emphasis mine), she seems to either not be very careful about her words, or rather disingenuous about what point she seems to be making. I’m not saying there are absolutely no effects to porn, but the research she presents do not make a good case for any of them.

References: Ferguson, C. & Hartley, R. (2009). The pleasure is momentary…the expense damnable? The influence of pornography on rape and sexual assault. Aggression & Violent Behavior, 14, 323-329.

Gwinn, A., Lambert N., Fincham, F., Maner, J. (2013). Pornography, relationship alternatives, and intimate extradyadic behavior. Social Psychology & Personality Science, 4, 699-704.

Lambert, N., Negash, S., Stillman, T., Olmstead, S., & Fincham, F. (2012). A love that doesn’t last: Pornography consumption and weakened commitment to one’s romantic partner. Journal of Social and Clinical Psychology, 31, 410-438.

Maddox, M., Rhoades, G., & Markman, H. (2011). Viewing sexually-explicit materials alone or together: Associations with relationship quality. Archives of Sexual Behavior, 40, 441-448.

Some Free Consulting Advice For Improving Online Dating

I find many aspects of life today to be pretty neat, owing largely to the wide array of fun and functional gadgets we have at our disposal. While easy to lose sight of and take for granted, the radical improvements made to information technology over my lifetime have been astounding. For instance, I now carry around a powerful computer in my pocket that is user-friendly, capable of accessing more information than I could feasibly process in my entire lifetime, and it also allows me to communicate instantly with strangers and friends all over the globe; truly amazing stuff. Of course, being the particular species that we are, such technology was almost instantly recognized and adopted as an efficient way of sending and receiving naked pictures, as well as trying to initiate new sexual or dating relationships. While the former goal has been achieved with a rousing success, the latter appears to still pose a few more complications, as evidenced by plenty of people complaining about online dating, but not about the ease by which they can send or receive naked pictures. As I’ve been turning my eye towards the job market these days, I decided it would be fun to try and focus on a more “applied” problem: specifically, how might online dating sites – like Tinder and OkCupid – be improved for their users?

Since the insertable portion of the internet market has been covered, I’ll stick to the psychological one.

The first question to consider is the matter of what problems people face when it comes to online dating: knowing what problems people are facing is obviously important if you want to make forward progress. Given that we are species in which females tend to provide the brunt of the obligate parental investment, we can say that, in general, men and women will tend to face some different problems when it comes to online dating; problems which mirror those faced in non-internet dating. In general, men are the more sexually-eager sex: accordingly, men tend to face the problem of drawing and retaining female interest, while women face the problem of selecting mates from among their choices. In terms of the everyday realities of online dating, this translates into women receiving incredible amounts of undesirable male attention, while men waste similar amounts of time making passes that are unlikely to pan out.

To get a sense for the problems women face, all one has to do is make an online dating profile as a woman. There have been a number of such attempts that have been documented, and the results are often the same: before the profile has even been filled out, it attracts dozens of men within the first few minutes of its existence. Perhaps unsurprisingly, the quality of messages that the profiles receive can also liberally be considered less-than optimal. While I have no data on the matter, almost every women who has talked with me about their online dating experiences tends to remark, at some point, that they are rather afraid of meeting up with anyone from the site owing to a fear of being murdered by them. Now it is possible that such dangers are, for whatever reason, being overestimated by women, but it also seems likely that women’s experiences with the men on the site might be driving some of that fear. After all, many of those same women also tell me that they start off replying to all or most of the messages they receive when they set up a profile, only to quickly stop doing that owing to their sheer volume or unappealing content. There are also reports of men becoming verbally aggressive when turned down by women, so it seems likely some of these fears about meeting someone from the site are not entirely without merit (to be clear, I think women are probably no more likely to be murdered by anyone they meet online relative to in person; it’s just that strangers online might be more likely to initiate contact than in person).

The problems that men face are a bit harder to appreciate for a number of reasons, one of which is likely owing to the fact that they take longer to appreciate. As I mentioned, women’s profiles attract attention within minutes of their creation; a rather dramatic effect. By contrast, were one to make a profile as a man, not much of anything would happen: you would be unlikely to receive messages or visitors for days, weeks, or months if you didn’t actively try to initiate such contact yourself. If you did try to initiate contact, you’d also find that most of it is not reciprocated and, of the replies you did receive, many would burn out before progressing into any real conversation. If men seen a bit overeager for contact and angry when it ceases, this might owe itself in part to the rarity with which such contact occurs. While being ignored might seem like a better problem to have than receiving a lot of unwanted attention (as the latter might involve aggression, whereas the former does not), one needs to bear in mind that without any attention there is no dating life. Women might be able to pull some desirable men from the pool of interested ones, even if most are undesirable; a man without an interested pool has no potential to draw from at all. Neither is necessarily better or worse than the other; they’re just different.

Relationships: Can’t live with them; can’t live without them

That said, bickering about whose problems are worse doesn’t actually solve any of them, so I don’t want to get mired in that debate. Instead, we want to ask, how do we devise a possible resolution to both sets of problems at the same time? At first glance, these problems might see opposed to one another: men want more attention and women want less of it. How could we make both sides relatively better off than they were before? My suggestion for a potential remedy is to make messages substantially harder to send. There are two ways I envision this might enacted: on the one hand, the number of messages a user could send (that were not replies to existing messages) could be limited  to a certain number in a given time period (say, for instance, people could send 5 or 10 initiate messages per week). Alternatively, people could set up a series of multiple choice screening questions on their profile, and only those people who answered enough questions “correctly” (i.e. the answer the user specifies) would be allowed to send a message to the user. Since these aren’t mutually exclusive, both could be implemented; perhaps the former as a mandatory restriction and the latter as an optional one.

Now, at first glance, these solutions might seem geared towards improving women’s experiences with online dating at the expense of men, since men are the ones sending most of the messages. If men aren’t allowed to send enough messages, how could they possibly garner attention, given that so many messages ultimately fail to capture any? The answer to that question comes in two parts, but it largely involves considering why so many messages don’t get responses. First, as it stands now, messaging is largely a costless endeavor. It can take someone all of 5 to 60 seconds to craft an opening message and send it, depending on how specific the sender wants to get with it. With such a low cost and a potentially high payoff (dates and/or sex), men are incentivized to send a great many of these messages. The problem is that every man is similarly incentivized. While it might be good for any man to send more messages out, when too many of them do it, women get buried beneath an avalanche of them. Since these messages are costless to send, they don’t necessarily carry any honest information about the man’s interest, so women might just start ignoring them altogether. There are, after all, non-negligible search costs for women to dig through and respond to all these messages – as evidenced by the many reports from women of their of starting out replying to all of them but quickly abandoning that idea – so the high volume of messages might actually make women less likely to respond in general, rather than more.

Indeed, judging by their profiles, many women pick up on this, explicitly stating that they won’t reply to messages that are little more than a “hey” or “what’s up?”. If messaging was restricted in some rather costly way, it would require men to be more judicious about both who they send the message to and the content of those messages; if you only have a certain number of opportunities, it’s best to not blow them, and that involves messaging people you’re more likely to be successful with in and in a less superficial way. So women, broadly speaking, would benefit by receiving a smaller number of higher-quality messages from men who are proportionately more interested in them. Since the messages are not longer costless to send, that a man chose to send his to that particular woman has some signal value; if the message was more personalized, the signal value increases. By contrast, men would, again, broadly speaking, benefit by lowering the odds of their messages being buried beneath a tidal wave of other messages from other men, and would need to send proportionately fewer of them to receive responses. In other words, the relative level of competition for mates might remain constant, but the absolute level of competition might fall.

Or, phrased as a metaphor: no one is responding to all that mess, so it’s better to not make it in the first place

Now, it should go without saying that this change, however implemented, would be a far cry from fixing all the interactions on dating sites: some people are less attractive than others, have dismal personalities, demand too much, and so on. Some women would continue to receive too many unwanted messages and some men would continue to be all but nonexistent as far as women were concerned. There would also undoubtedly be some potential missed connections. However, it’s important to bear in mind that all that happens already, and this solution might actually reduce the incidence of it. By everyone being willing to suffer a small cost (or the site administrators implementing them), they could avoid proportionately larger ones. Further, if dating sites became more user-friendly, they could also begin to attract new users and retain existing ones, improving the overall dating pool available. If women are less afraid of being murdered on dates, they might be more likely to go on them; if women receive fewer messages, they might be more inclined to respond to them. As I see it, this is a relatively cheap idea to implement and seems to have a great deal of theoretical plausibility to it. The specifics of the plan would need to be fleshed out more extensively and it’s plausibility tested empirically, but I think it’s a good starting point.

Practice Makes Better, But Not Necessarily Much Better

“But I’m not good at anything!” Well, I have good news — throw enough hours of repetition at it and you can get sort of good at anything…It took 13 years for me to get good enough to make the New York Times best-seller list. It took me probably 20,000 hours of practice to sand the edges off my sucking.” -David Wong

That quote is from one of my favorite short pieces of writing entitled “6 Harsh Truths That Will Make You a Better Person”, which you can find linked above. The jist of the article is simple: the world (or, more precisely, the people in the world) only care about what valuable things you provide them, and what is on the inside, so to speak, only matters to the extent that it makes you do useful things for others. This captures nicely some of the logic of evolutionary theory – a piece that many people seem to not appreciate – namely that evolution cannot “see” what you feel; it can only “see” what organisms do (seeing, in this sense, referring to selecting for variants that do reproductively-useful things). No matter how happy you are in life, if you aren’t reproducing, whatever genes contributed to that happiness will not see the next generation. Given that your competence at performing a task is often directly related to the value it could potentially provide for others, the natural question many people begin to consider is, “how can I get better at doing things?”

  Step 1: Print fake diploma for the illusion of achievement

The typical answer to that question, as David mentions, is practice: by throwing enough hours of practice at something, people tend to get sort of good at it. The “sort of” in that last sentence is rather important, according to a recent meta-analysis. The paper – by Macnamara et al (2014) – examines the extent of that “sort of” across a variety of different studies tracking different domains of skill one might practice, as well as across a variety of different reporting styles concerning that practice. The results from the paper that will probably come as little surprise to anyone is that – as intuition might suggest – the amount of time one spends practicing does, on the whole, seem to show a positive correlation with performance; the ones that probably will come as a surprise is that the extent of that benefit explains a relatively-small percentage of the variance in eventual performance between people.

Before getting into the specific results of the paper, it’s worth noting that, as a theoretical matter, there are reasons we might expect practicing on a task to correlate with eventual performance even if the practicing itself has little effect: people might stop practicing things they don’t think they’re very good at doing. Let’s say I wanted to get myself as close to whatever the chess-equivalent of a rockstar happens to be. After playing the game for around a month, I find that, despite my best efforts, I seem to be losing; a lot. While it is true that more practice playing chess might indeed improve my performance to some degree, I might rightly conclude that investing the required time really won’t end up being worth the payoff. Spending 10,000 hours of practice to go from a 15% win rate to a 25% win rate won’t net me any chess groupies. If my time spent practicing chess is, all things considered, a bad investment, not investing anymore time in it than I already had would be a rather useful thing to do, even if it might lead to some gains. The idea that one ought to persist at the task despite the improbable nature of a positive outcome (“if at first you don’t succeed, try, try again”) is as optimistic as it is wasteful. That’s not a call to give up on doing things altogether, of course; just a recognition that my time might be profitably invested in other domains with better payoffs. Then again, I majored in psychology instead of computer science or finance, so maybe I’m not the best person to be telling anyone else about profitable payoffs…

In any case, turning to the meat of the paper, the authors began by locating around 9,300 articles that might have been relevant to their analysis. As it turns out, only 88 of them possessed the relevant inclusion criteria: (1) an estimate of the numbers of hours spent practicing, (2) a measure of performance level, (3) and effect size of the relationship between those first two things, (4) written in English, and (5) conducted on humans. These 88 studies contained 111 samples, 157 effect sizes, and approximately 11,000 participants. Of those 157 correlations, 147 of them were positive: as performance increased, so too did hours of practice tend to increase in an overwhelming majority of the papers. The average correlation between hours of practice and performance was a 0.35. This means that, overall, deliberate practice explained around 12% of the variance in performance. Throw enough hours of repetition at something and you can get sort of better at it. Well, somewhat slightly better at it, anyway…sometimes…

At least it only took a few decades of practice to realize that mediocrity

The average correlation doesn’t give a full sense of the picture, as many averages tend to not. Macnamera et al (2014) first began to break the analysis down by domain, as practicing certain tasks might yield greater improve than others. The largest gains were seen in the realm of games, where hours of practice could explain around a forth of the variance in performance. From there, the percentages decreased to 21% in music, 18% in sports, 4% in education, and less than 1% in professions. Further, as one might also expect, practice showed the greatest effect when the tasks were classified as highly predictable (24% of the variance), followed by moderately (12%) and poorly predictable (4%). If you don’t know what to expect, it’s awfully difficult to know what or how to practice to achieve a good outcome. Then again, even if you do know what to expect, it still seems hard to achieve those outcomes.

Somewhat troubling, however, was that the type of reporting about practicing seemed to have a sizable effect as well: reports that relied on retrospective interviews (i.e. “how often would you say you have practiced over the last X weeks/months/years”) tended to show larger effects; around 20% of the variance explained. When the method was a retrospective questionnaire, rather than an interview, this dropped to 12%. For the studies that actually involved keeping daily logs of practice, this percentage dropped precipitously to a mere 5%. So it seems at least plausible that people might over-report how much time they spend practicing, especially in a face-to-face context. Further still, the extent of the relationship between practice and product depended heavily on the way performance was measured. For the studies simply using “group membership” as the measure of skill, around 26% of the variance was explained. This fell to 14% when laboratory studies alone were considered, and fell further when expert ratings (9%) or standardized measures of performance (8%) were used.

Not only might be people be overestimating how much time they spend practicing a skill, then, but the increase in ability possibly attributable to that practice appears to shrink the more fine-grained or specific an analysis gets. Now it’s worth mentioning that this analysis is not able to answer the question of how much improvement in performance is attributable to practice in some kind of absolute sense; it just deals with how much of the existing differences between people’s ability might be attributable to differences in practice. To make that point clear, imagine a population of people who were never allowed to practice basketball at all, but were asked to play the game anyway. Some people will likely be better than others owing to a variety of factors (like height, speed, fine motor control, etc), but none of that variance would be attributable to practice. It doesn’t mean that people wouldn’t get better if they were allowed to practice, of course; just that none of the current variation would be able to be chalked up to it.

And life has a habit of not being equitable

As per the initial quote, this paper suggests that deliberate practicing, at least past a certain point, might have more to do with sanding the harsh edges off one’s ability rather than actually carving it out. The extent of that sanding likely depends on a lot of things: interests, existing ability, working memory, general cognitive functioning, what kind of skill is in question, and so on. In short, it’s probably not simply a degree of practice that separates a non-musician from Mozart. What extensive practice can help with seems to be more pushing the good towards the great. As nice as it sounds to tell people that they can achieve anything they put their mind to, nice does not equal true. That said, if you have a passion for something and just wish to get better at it (and the task at hand lends itself to improvement via practice), the ability to improve performance by a few percentage points is perfectly respectable. Being slightly better at something can, on the margins, mean the difference between winning or losing (in whatever form that takes); it’s just that all the optimism and training montages in the world probably won’t take you from the middle to the top.

References: Macnamera, B., Hambrick, D., & Oswald, F. (2014). Deliberate practice and performance in music, games, sports, education, and professions: A meta-analysis. Psychological Science, DOI: 10.1177/0956797614535810

Keepin’ It Topical: The Big Facebook Study

I happen to have an iPhone because, as many of you know, I think differently (not to be confused with the oddly-phrased “Think Different”® slogan of the parent company, Apple), and nothing expresses those characteristics of intelligence and individuality about me better than my ownership of one of the most popular phones on the market. While the iPhone itself is a rather functional piece of technology, there is something about it (OK; related to it) that has consistently bothered me: the Facebook app I can download for it. The reason this app has been bugging me is that, at least as far as my recent memory allows, the app seems to have an unhealthy obsession with showing me the always-useless “top stories” news feed as my default, rather than the “most recent” feed I actually want to see. In fact, I recall that the last update to the app actually made it more of a hassle to get to the most recent feed, rather than make it easily accessible. I had always wondered why there didn’t seem to be a simple way to change my default, as this seems like a fairly basic design fix. Not to get too conspiratorial about the whole thing, but this past week, I think I might have found part of the answer.

Which brings us to the matter of the Illuminati…

It’s my suspicion that the “top stories” feed has uses beyond simply trying to figure out which content I might want to see; this would be a good thing, because if the function were to figure out what I want to see, it’s pretty bad at that task. The “top stories” feed might also be used for the sinister purposes of conducting research (then again, the “most recent” feed can probably do that as well; I just really enjoy complaining about the “top stories” one). Since this new story (or is it a “top story”?) about Facebook conducting research with its users has been making the rounds in the media lately, I figured I would add my two cents to the incredibly tall stack of pennies the internet has collectively made in honor of the matter. Don’t get it twisted, though: I’m certainly not doing this in the interest of click-bait to capitalize on a flavor-of-the-week topic. If I were, I would have titled this post “These three things about the Facebook study will blow your mind; the fourth will make you cry” and put it up on Buzzfeed. Such behavior is beneath me because, as I said initially, I think different(ly)…

Anyway, onto the paper itself. Kramer et al (2014) set out to study whether manipulating what kind of emotional content people are exposed to in  other’s Facebook status updates had an effect on that person’s later emotional content in their own status updates. The authors believe such an effect would obtain owing to “emotional contagion”, which is the idea that people can “…transfer positive and negative moods and emotions to others”. As an initial semantic note, I think that such phrasing – the use of contagion as a metaphor – only serves to lead one to think incorrectly about what’s going on here. Emotions and moods are not the kind of things that can be contagious the way pathogens are: pathogens can be physically transferred from one host to another, while moods and emotions cannot. Instead, moods and emotions are things generated by our minds from particular sets of inputs.

To understand that distinction quickly, consider two examples: in the first case, you and I are friends. You are sad and I see you being sad. This, in turn, makes me feel sad. Have your emotions “infected” me? Probably not; consider what would happen if you and I were enemies instead: since I’m a bastard and I like to see people I don’t like fail, your sadness might make me feel happy instead. So it doesn’t seem to be your emotion per se that’s contagious; it might just be the case that I happen to generate similar emotions under certain circumstances. While this might seem to be a relatively minor issue, similar types of thinking about the topic of ideas – specifically, that ideas themselves can be contagious – has led to a lot of rather unproductive thinking and discussions about “memes”. By talking about ideas or moods independently of the minds that create them, we end up with a rather dim view of how our psychology works, I feel.

Which is just what the Illuminati want…

Moving past that issue, however, the study itself is rather simple: for a week in 2012, approximately 700,000 Facebook users had some of their news feed content hidden from them some of the time. Each time one of the subjects viewed their feed, depending on what condition they were in, each post containing certain negative or positive words had a certain probability (between 10-90% chance) of being omitted. Unfortunately, the way the paper is written, it’s a bit difficult to get a sense as to precisely how much content was, on average, omitted. However, as the authors note, this was done a per-viewing basis, so content that was hidden during one viewing might well have showed up were the page to be refreshed (and sitting there refreshing Facebook minute after minute is something many people might actually do). The content was also only hidden on the news feed: if the subject visited a friend’s page directly or sent or received any messages, all the content was available. So, for a week, some of the time, some of the content was omitted, but only on a per-view basis, and only in one particular form (the news feed); not exactly the strongest manipulation I could think of.

The effect of that manipulation was seen when examining what percentage of positive or negative words the subjects themselves used when posting their status updates during the experimental period. Those subjects who saw more positive words in their feed tended to post more positive words themselves, and vice versa for negative words. Sort of, anyway. OK; just barely. In the condition where subjects had access to fewer negative words, the average subject’s status was made up of about 5.3% positive words and 1.7% negative words; when the subjects had access to fewer positive words, these percentages plummeted/jumped to…5.15% and 1.75%, respectively. Compared to the control groups, then, these changes amount to increases or decreases of in between 0.02 and 0.0001 standard deviations of emotional word usage or, as we might say in precise statistical terms, effects so astonishingly small they might as well not be said to exist.

“Can’t you see it? The effect is right there; plain as day!”

What we have here, in sum, then, is an exceedingly weak and probabilistic manipulation that had about as close to no net effect as one could reasonably get, based on an at-least-partially (if only metaphorically) deficient view of how the mind works. The discussion about the ethical issues people perceived with the research appears to have vastly overshadowed the fact that research itself wasn’t really very strong or interesting. So for all of you people outraged over this study for fear that people were harmed: don’t worry. I would say the evidence is good that no appreciable harm came of it.

I would also say that other ethical criticisms of the study are a bit lacking. I’ve seen people raise concerns that Facebook had no business seeing if bad moods would be induced by showing people a disproportionate number of negative status updates; I’ve also seen concerns that the people posting these negative updates might not have received the support they needed if other people were blocked from seeing them. The first thing to note is that Facebook did not increase the absolute number of positive or negative posts; only (kind of) hid some of them from appearing (some of the time, to some people, in one particular forum); the second is that, given those two criticisms, it would seem that Facebook is in a no-win situation: reducing or failing to reduce the number of negative stories leads to them being criticized. Facebook is either failing to get people the help they need or bumming us out by disproportionately exposing us to people who need help. Finally, I would add that if anyone did miss a major life event of a friend – positive or negative – because Facebook might have probabilistically omitted a status update on a given visit, then you’re likely not very good friends with that person anyway, and probably don’t have a close enough relationship with them that would allow you to realistically lend help or take much pleasure from the incident.

References: Kramer, A., Guillory, J., & Hancock, J. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedings of the National Academy of Sciences of the United States of America, doi: 10.1073/pnas.1320040111

Where Did I Leave My Arousal?

Jack is your average, single man. Like many single men, Jack might be said to have an interest in getting laid. There are a number of women – and let’s just say they all happen to be called Jill – that he might attempt to pursue to achieve that goal. Now which of these Jills Jack will pursue depends a number of factors: first, is Jack looking for something more short-term and causal, or is he looking for a long-term relationship? Jack might want to consider whether or not any given Jill is currently single, known for promiscuity, or attractive, regardless of which type he’s looking for. If he’s looking for something more long-term, he might also want to know more about how intelligent and kind all these Jills are. He might also wish to assess how interested each of the Jills happens to be in him, given what he offers, as he might otherwise spend a lot of time pursuing sexual dead-ends. If he really wanted to make a good decision, though, Jack might also wish to take into account whether or not he happened to have been scared at the time he met a given Jill, as his fear level at the time is no doubt a useful piece of information.

“Almost getting murdered was much more of a turn-on than I expected”

OK; so maybe that last piece sounded a bit strange. After all, it doesn’t seem like Jack’s experience of fear tells him anything of value when it comes to trying to find a Jill: it doesn’t tell him anything about that Jill as a suitable mate or the probability that he will successfully hook up with her. In fact, by using his level of fear to an unrelated issue to try and make a mating decision, it seems Jack can only make a worse decision than if he did not use that piece of information (on the whole, anyway; his estimates of which Jill(s) are his best bet to pursue might not be entirely accurate, but they’re at least based on otherwise-relevant information). Jack might as well make his decision about who to pursue on the basis of whether he happened to be hungry when he met them or whether it was cloudy that day. However, what if Jack – or some part of Jack’s brain, more precisely – mistook the arousal he felt when he was afraid for sexual attraction?

There’s an idea floating around in some psychological circles that one can, essentially, misplace their arousal (perhaps in the way one misplaces their keys: you think you left them on the steps, but they’re actually in your coat pocket). What this means is that someone who might be aroused due to fear might end up thinking they’re actually rather attracted to someone else instead, because both of those things – fear and sexual attraction – involve physiological arousal (in the form of things like an increased heart rate); apparently, physiological arousal is pretty vague and confusing thing for our brains. One study purporting to show this effect is a classic paper covered in many psychological textbooks: Dutton & Aron (1974). In the most famous experiment of the study, 85 men were approached by a confederate (either a man or a woman) after crossing a fear-inducing bridge or a non-fear-inducing bridge. The men were given a quick survey and asked to write a short story about an ambiguous image of a woman, after which the confederate provides the men with their number if they want to call and discuss the study further. The idea here is that the men might call if they were interested in a date, rather than the study, which seems reasonable.

When the men’s stories were assess for sexual content, those who had crossed the fear-inducing bridge tended to write stories containing more sexual content (M = 2.47 out of 5) compared to when they crossed the non-fear-inducing bridge (M = 1.41). However, this was only the case when the confederate was female; when a male confederate was administering the questions, there was no difference between the two condition in terms of sexual content (M = 0.8 and 0.61, respectively). Similarly, the male subjects were more likely to call the confederate following the interaction when crossing the fear bridge (39%), relative to the non-fear bridge (9%). Again, this difference was only significant when the confederate was a female; male confederates were called at the same rate (8% and 4.5%, respectively).  Dutton & Aron (1974) suggest that these results were consistent with a type of “cognitive relabeling”, where the arousal from fear becomes reinterpreted by the subjects as sexual attraction. The authors further (seem to, anyway) suggest that this relabeling might be useful because anxiety and fear are unpleasant things to feel, so by labeling them as sexual attraction, subjects get to feel good things (like horny) instead.

“There we go; much better”

These explanations – that the mind mistakes fear arousal for sexual arousal, and that this is useful because it makes people feel good – are both theoretically deficient, and in big ways. To understand why with a single example, let’s consider a hiker out in the wood who encounters a bear. Now this bear is none-too-happy to see the hiker and begins to charge at him. The hiker will, undoubtedly, experience a great deal of physiological arousal. So, what would happen if the hiker mistook his fear for sexual interest? At best, he would end up achieving an unproductive copulation; at worse, he would end up inside the bear, but not in the way he might have hoped. The first point to this example, then, is that the appropriate responses to fear and sexual attraction are quite different: fear should motivate you to avoid, escape, or defend against a threat, whereas sexual attraction should motivate you to more towards the object of your desires instead. Any cognitive system that could easily blur the lines between these two (and other) types of arousal would appear to be at a disadvantage, relative to one that did not make such mistakes. We would end up running away from our dates into the arms of bears. Unproductive indeed.

The second, related point is that feeling good per se does not do anything useful. I might feel better if I never experienced hunger; I might also starve to death, despite being perfectly content about the situation. As such, “anxiety-reduction” is not even a plausible function for this ostensible cognitive relabeling. If anxiety reduction were a plausible function, one would be left wondering why people bothered to feel anxiety in the first place: it seems easier to not bother feeling anxiety than to have one mechanism that – unproductively – generates it, and a second which quashes it. What we need here, then, is an entirely different type of explanation to understand these results; one that doesn’t rely on biologically-implausible functions or rather sloppy cognitive design. To understand what that explanation might look like, we could consider the following comic:

“I will take a prostitute, though, if you happen to have one…”

The joke here, obviously, is that the refusal of a cigarette prior to execution by firing squad for health reasons is silly; it only makes sense to worry about one’s health in the future if there is a future to worry about. Accordingly, we might predict that people who face (or at least perceive) uncertainty about their future might be less willing to forgo current benefits for future rewards. That is, they should be more focused on achieving short-term rewards: they might be more likely to use drugs, less likely to save money, less likely to diet, more likely to seek the protection of others, and more likely to have affairs if the opportunity arose. They would do all this not because they “mistook” their arousal from fear about the future for sexual attraction, pleasant tastes, friendship, and fiscal irresponsibility, but rather because information about their likely future has shifted the balance of preexisting cost/benefit ratios in favor of certain alternatives. They know that the cigarette would be bad for their future health, but there’s less of a future to worry about, so they might as well get the benefits of smoking while they can.

Such an explanation is necessarily speculative and incomplete (owing to this being a blog and not a theory piece), but it would certainly begin to help explain why people in relationships don’t seem to “mistake” their arousal from riding a roller-coaster for heightened levels of stranger attractiveness the way single people do (Meston & Frohlich, 2003). Not only that, but those in relationships didn’t rate their partners as any more attractive either; in fact, if anything, the aroused roller-coaster riders in committed relationships rated their partners as slightly less attractive, which might represent a subtle shift in one’s weighing of an existing cost/benefit ratio (related to commitment, in this case) in the light of new information about the future. Then again, maybe people in relationships are just less likely to misplace their arousal than single folk happen to be…

References: Dutton, D. & Aron, A. (1974). Some evidence for heightened sexual attraction under conditions of high anxiety. Journal of Personality and Social Psychology, 30, 510-517.

Meston, C. & Frohlich, P. (2003). Love at first fright: Partner salience moderates roller-coaster-induced excitation transfer. Archives of Sexual Behavior, 32, 537-544.

Up Next On MythBusters: Race And Parenting

Lately, there’s been an article that keeps crossing my field of vision; it’s done so about three or four times in the last week, likely because it was written about fathers and father’s day has just come and gone. The article is titled, “The Myth of the Absent Black Father“. In it, Tara Culp-Ressler suggests that “hands-on parenting is similar among dads of all races”, and, I think, that the idea that any racial differences in the parenting realm might exist is driven by inaccurate racist stereotypes instead of accurate perceptions of reality. There are two points I want to make, one of which is specific to the article itself, and the other of which is about stereotypes and biases as they are spoken about more generally. So let’s start with the myth-busting about parenting across races.

Network TV wasn’t touching this one with a 10-foot pole

The first point I want to make about the article in question is that the title is badly at odds with the data being reported on. The title – The Myth of the Absent Black Father – would seem to strongly suggest that the myth here is that black fathers tend to be absent when it comes to childcare (presumably with respect to other racial groups, rather than in some absolute sense of the word). Now if one wished to label this a myth, they should, presumably, examine the data of the percentage of families with father-present and father-absent homes to demonstrate that rates of absent fathers do not differ substantially by race. What it means to be “present” or “absent” is, of course, a semantic issue that is likely to garner some disagreement. In the interests of maintaining something resembling a precise definition, then, let’s consider matters over which there is likely to be less disagreement, such as, “across different races, are the fathers equally likely to be married to the mother of their children?” or, “does the father live in the same household as their child?”.

There exists plenty of data that speaks to those questions. The answer from the data to both is a clear “no; fathers are not equally likely to be living with the mother across races”. According to census data from 2009, for instance, black children were residing in single-mother homes in around 50% of cases, compared to 18% of white children, 8% in Asian children, and 25% in Hispanic children. With respect to births outside of marriage, further data from 2011 found:

…72 percent of all births to black women, 66 percent to American Indian or Alaskan native women, and 53 percent to Hispanic women occurred outside of marriage, compared with 29 percent for white women, and 17 percent for Asian or Pacific Islander women.

In these two cases, then, it seems abundantly clear that, at least relatively speaking, the “myth” of absent black fathers is not a myth at all; it’s a statistical reality (just like how last time I was discussing “myths” about sex differences, most of the “myths” turned out to be true). This would make the title of the article seem more than a little misleading. If the “myth” of the absent black father isn’t referring to whether the father is actually present in the home or not, then what is the article focused on?

The article itself focuses on a report by the CDC which found that, when they are present, fathers tend to report being about equally involved in childcare over the last month, regardless of their race; similar findings emerge for fathers who are absent. In other words, an absent father is an absent father, regardless of race, just as a present father is a present father, regardless of race. There were some slight differences between racial groups, sure; but nothing terribly noteworthy. That said, if one is concerned with the myth of the absent black father, comparing how much work fathers do given they are present or absent  across races seems to miss the mark. Yes; present fathers tend to do more work than absent ones, but the absent ones are disproportionately represented in some groups. That point doesn’t seem to be contested by Tara; instead, she opts to suggest that the reasons that many black fathers don’t live with their children come down to social and economic inequalities. Now that explanation may well be true; it may well not be the whole picture, either. The reason(s) this difference exists is likely complicated, as many things related to human social life are. However, even fully explaining the reasons for a discrepancy does not make the discrepancy stop existing, nor does it make it a myth.

But never mind that; your ax won’t grind itself

So the content of the article is a bit of a non-sequitur from the title. The combination of the title and content seemed a bit like me trying to say it’s a myth that it’s cloudy outside because it’s not raining; though the two might be related, they’re not the same thing (and it very clearly is cloudy, in any case…). This brings me to the second, more general point I wanted to discuss: articles like these are common enough to be mundane. It doesn’t take much searching to find people writing about how (typically other) people (who the author disagrees with or dislikes) tend to hold to incorrect stereotypes or have fallen prey to cognitive biases. As Steven Pinker once said, a healthy portion of social psychological research often focuses on:

… endless demonstrations that People are Really Bad at X, which are then “explained” by an ever-lengthening list of Biases, Fallacies, Illusions, Neglects, Blindnesses, and Fundamental Errors, each of which restates the finding that people are really bad at X.

Reading over a lot of the standard psychological literature, one might get the sense that people aren’t terribly good at being right about the world. In fact, one might even get the impression that our brains were designed to be wrong about a number of socially-important things (like how smart, trustworthy, or productive some people are which might, in turn, affect our decisions about whether they would make good friends or romantic partners). If that were the case, it should pose us with a rather interesting biological mystery.

That’s not to say that being wrong per se is much of a mystery – as we lack perfect information and perfect information processing mechanisms – but rather that it would be strange if people’s brains were designed for such an outcome: if people’s minds were designed to make use of stereotypes as a source of information for decision making, and if those stereotypes are inaccurate, then people should be expected to make worse decisions relative to if they had not used that stereotype as information in the first place (and, importantly, that being wrong tends to carry fitness-relevant consequences). That people continue to make use of these stereotypes (regardless of their race or sex) would require an explanation. Now the most obvious reason for the usage of stereotypes would be, as per the example above, that they are not actually wrong. Before wondering why people use bad information to make decisions, it would serve us well to make sure that the information is, well, actually bad (again, not just imperfect, but actually incorrect).

“Bad information! Very bad!”

Unfortunately, as far as I’ve seen, proportionately-few projects on topics like biases and stereotypes begin by testing for accuracy. Instead, they seem to begin with their conclusion (which is generally, “people are wrong about quite a number of things related to gender and/or race, and no meaningful differences could possibly exist between these groups, so any differential treatment of said groups must be baseless”) and then go out in search of the confirmatory evidence. That’s not to say that all stereotypes will necessarily be true, of course; just that figuring out if that’s the case ought to be step one (step two might then involve trying to understand any differences that do emerge in some meaningful way, with the aforementioned knowledge that explaining these differences doesn’t make them disappear). Skipping that first step leads to labeling facts as “myths” or “racist stereotypes”, and that doesn’t get us anywhere we should want to be (though it can get one pretty good publicity, apparently).

Misinformation About Evolution In Textbooks

Throughout my years making my way through various programs at various schools, I have received (and I say this is the humblest way possible, which appears to be not very…) a number of compliments from others regarding my scholarship. People often seem genuinely impressed that I make the effort to read all the source material I reference and talk about. Indeed, when it came to the class I taught last semester, I did not review any research in class that I had not personally read in full beforehand, frequently more than once. Now, to me, this all seems relatively mundane: I feel that academics should make sure to read all the material they’re using before they use it, and that doing so should be so commonplace that it warrants no special attention. I don’t feel teachers should be teaching others about research they, like Jon Snow, know little or nothing about. Now I have no data regarding how often academics or non-academics do or do not try to teach others about or argue about research they have little personal familiarity with, but, if consulting source material was as common as I would hope, it would seem odd that I received explicit compliments about it on multiple occasions. Compliments are often reserved for special behaviors; not mundane ones.

 ”Thanks, Bob; it was really swell of you to not murder me”

It is for this reason that I have always been at least little skeptical of textbooks in psychology: many of these textbooks cover and attempt to provide some summary of large and diverse areas of research. This poses two very real questions, in my mind: (a) have the authors of these books really read and understood all the literature they are discussing, and (b) provided they have, are they going to be able to provide a summary of it approaching adequate in the space provided?  For instance, one of my undergraduate textbooks – Human Sexuality Today, by Bruce M. King (2005) – contains a reference section boasting about 40 pages, on each of which approximately 60 references are contained. Now perhaps Dr. King is intimately, or at least generally, familiar with all 2,400 references on that list and is able to provide a decent summary of them on the approximately 450 pages of the book; it’s not impossible, certainly.

There are some red flags to me that this is not the case, however. One thing I can now do, having some years of experience under my belt, is return to these books and examine the sections I am familiar with to see how well they’re covered. For instance, on page 254, King (2005) is discussing theories of gender roles. In that section, hes makes reference to two papers by Buss and Geary, but then, rather than discuss those papers, he cites a third paper, by Wood and Eagly, to summarize them. This seems like a rather peculiar choice; a bit like my asking someone else where you said you wanted to go eat when I could just ask you and, in fact, have a written transcript of where you said you wanted to go eat. On page 436, when discussing evolutionary theories of rape, King writes that Thornhill and Palmer’s book suggested that “women can provoke rape” (which the book does not) and that the evolutionary theory “does not explain why men rape children, older women, and other men” (demonstrating their lack of understanding about proximate/ultimate distinction). In fact, King goes on to mention a “thoughtful review” of Thornhill and Palmer’s book that suggests rape might be a byproduct and that “we must not confuse causation with motivation”. Thoughtful indeed. So thoughtful, in fact, that the authors of the book in question not only suggested that rape might be a byproduct, but the pair also take great pains to outline the distinction between proximate and ultimate causes. Issues like these do not appear to be the hallmark of a writer familiar with the topic they are writing about. (I will also note that, during the discussion on the function of masturbation, King writes, “Why do people masturbate? Quite simply, because it feels good” (p.336). I will leave it up to you to decide whether that explanation is particularly satisfying on a functional level).

Now these are only two errors, and I have neither the time nor the patience to sift through the full textbook to look for others, but there’s reason to think that this is by no means an isolated incident. I wrote previously about how evolutionary psychology tends to be misrepresented in introductory psychology textbooks and, when it is mentioned, is often confined to only a select topic or two. These frequent errors are, again, not the hallmarks of people who are terribly familiar with the subjects they are supposed to be educating others about. To the extent that people are being educated by books like these, or using them to educate others, this poses a number of obvious problems concerning the quality of that education, along with a number of questions along the lines of, “why am I trusting you to educate me?” To drive that point home a bit further, today we have another recent paper for consideration by Winegard et al (2014), who examined the representation of evolutionary psychology within 15 popular sex and gender textbooks in psychology and sociology. Since the most common information people seem to hear about evolutionary psychology does concern sex and gender, they might represent a particularly valuable target to examine.

“Don’t worry; I’m sure they’ll nail it”

The authors begin by noting that previous analyzes of evolutionary psychology’s representation in undergraduate textbooks has been less-than stellar, with somewhere between “a lot” and “all” of the textbooks that have been examined showing evidence of errors, a minority showing hostility, and that’s all provided the subject was even mentioned in the first place; not a good start. Nevertheless, the authors collected a sample of 15 academic textbooks from 2005 or later – six in sociology and nine in psychology – that saw some fairly regular use: out of a sample of around 1,500 sociology courses, one of those six books was used in about half of them, and a similar percentage of 1,200 psychology courses sampled used one of the nine psychology texts. The most widely-used of these texts were in around 20% and 10% of courses, respectively, so these books were seeing some fairly good popularity.

Of these 15 books, 3 did not discuss the theoretical foundations of evolutionary psychology and were discarded from the analysis; the remaining 12 books were examined for the areas in which evolutionary psychology was discussed, and any errors they made were cataloged. Of those 12 books, all of them contained at least one error, with the average number of errors per book hovering around 5 (allowing for the fact that they could make the same error more than once), with an average of 4 different categories of error per book. The most common of these errors, unsurprisingly, was the umbrella “strawman” category, where positions not held by evolutionary psychology are said to be representative of their actual positions (I believe the Thornhill and Palmer suggesting women “provoke rape” would fall into this category). The number of errors might not seem all that large at first glance, but once one considers that the average number of pages within the textbooks under consideration were around 6 for psychology and 3 for sociology, that’s around one or two errors a page.

Additionally, the errors that the authors found within these textbooks are cataloged at the end of their paper. Reading through the list should be more than little frustrating, if an entirely familiar experience, for anyone even moderately well-versed in evolutionary psychology. In accordance with the masturbation example listed above, there’s more than one instance in that list of writers suggesting that evolutionary researchers ignore the fact that people have sex for pleasure because we only focus on reproduction (for another example of this error, see here). Now there’s nothing wrong with being critical of evolutionary psychology, to be clear; criticisms are often the lifeblood of advancements. It is important, however, that one is at least familiar with the ideas they are going to be critical towards before attempting criticism, or the education of, others. This should sound like a basic point, but, then again, reading source material you’re discussing shouldn’t be something noteworthy that one gets compliments about.

“As long I don’t read it, I can still disagree with what I think it says…”

These are, of course, just the errors; there’s no consideration here of the degree to which topics are covered in sufficient depth. To the extent that people – teachers and undergraduates alike – are receiving an education from (or creating one based on) these textbooks, we should expect to see these errors repeated. In this case, we might actually hope that students are not reading their books since, in my mind, no education on the subject is likely better than a false sense of one. Now one might make the case that the authors of these textbooks don’t have the time to read everything they cite or cover it in the detail required for it to be of much use, meaning that we should expect errors like these to crop up. If that’s the case, though, it’s curious why anyone would rely on these textbooks as worthwhile sources of information. To put it in metaphorical terms, when it comes to providing information about EP, these textbooks seem about as a good as a tour of Paris taken via plane with a guide who have never been their himself. Not only is the experience unlikely to give you much of a sense for the city, it’s not the type of thing I would pay a lot of money for. While I certainly can’t speak to how well other topics are covered, I think there might be good reason to worry as well.

References: King, B. (2005). Human Sexuality Today. Pearson, NJ.

Winegard B., Winegard, B., & Deaner, R. (2014). Misrepresentations of evolutionary psychology in sex and gender textbooks. Evolutionary Psychology, 12, 474-508.

Punch-Ups In Bars

For those of you unfamiliar with the literature in economics, there is a type of experimental paradigm called the dictator game. In this game, there are two players, one of which is given a sum of money and told they can do whatever they want with it. They could keep it all for themselves, or they could divide it however they want between themselves and the other player. In general, you often find that many dictators – the ones in charge of dividing the money – give at least some of the wealth to the other player, with many people sharing it evenly. Some people have taken that finding to suggest there is something intrinsically altruistic about human behavior towards others, even strangers. There are, however, some concerns regarding what those results actually tell us. For instance, when you take the game out of the lab and into a more naturalistic setting, dictators don’t really tend to give other people any money at all, suggesting that most, or perhaps all, of the giving we see in these experiments is being driven by the demand characteristics of the experiment, rather than altruism per se. This should ring true to anyone who has even had a wallet full of money and not given some of it away to a stranger for no reason. Real life, it would seem, is quite unlike dictator games in many respects.

Dictators are not historically known for their benevolence.

Relatedly, around two years ago, Rob Kurzban wondered to what extent the role of ostensibly altruistic punishment had been overstated by laboratory experiments. Altruistic punishment refers to cases in which someone – the punisher – will incur costs themselves (typically by paying a sum of money in these experiments) to inflict costs on others (typically by deducting a sum of money from another person). What inspired this wondering was a video entitled “bike thief“, where a man tries to steal his own bike, using a crowbar, hacksaw, and power tool to cut the locks securing the bike to various objects. Though many people pass by the man as he tries to “steal” his bike, almost no one intervenes to try and determine what’s going on. This video appears to show the same pattern of results as a previous one also dealing with bike theft: in that video, third parties are somewhat more likely to intervene when a white man tries to steal the bike than in the first video one, but, in general, they don’t tend to involve themselves much, if at all (they are more likely to intervene if the ostensible thief is black or a woman. In the former case, people are more likely to confront him or call the police; in the latter case, some people intervened to help the woman, not to condemn her).

I have long found these videos fascinating, in that I feel they raise a lot of questions worthy of further consideration. The first of these is how do people decide when to become involved in the affairs of others? The act itself (sawing through a bike lock) is inherently ambiguous: is the person trying to steal the bike, or is the bike theirs but they have lost the key? Further, even if the person is stealing the bike, there are certain potential risks to confronting them about it that might be better avoided. The second question is, given someone has decided to become involved, what do they do? Do they help or hinder the thief? Indeed, when the “thief” suggests that they lost the key, the third parties passing by seem willing to help, even when the thief is black; similarly, even when the woman all but says she is stealing the bike, people (typically men) continue to help her out. When third parties opt instead to punish someone, do they do so themselves, or do they try to enlist others to do the punishing (like police and additional third parties)? These two questions get at the matter of how prevalent/important is third-party punishment outside of the lab, and under what circumstance might that importance be modified?

Though there is a lack of control one faces from moving outside of the lab into naturalistic field studies, the value of these studies for understanding punishment should be hard to overstate. As we saw initially with the dictator games, it is possible that all the altruistic behavior we observe in the lab is due to experimental demand characteristics; the same might be true of third-party moral condemnation. Admittedly, naturalistic observations of third-party involvement in conflicts is rare, likely owing to how difficult it is to get good observations of immoral acts that people might prefer you didn’t see (i.e. real bike thieves likely go through some pains to not be seen so others might be unlikely to become involved, unlike the actors in the videos). One particularly useful context for gathering these observations, then, is one in which the immoral act is unlikely to be planned and people’s inhibitions are reduced: in this case, when people are drinking at bars. As almost anyone who has been out to a bar can tell you, when people are drinking tempers can flare, people overstep boundaries, and conflicts break out. When that happens, there often tends to be a number of uninvolved third parties who might intervene, making it a fairly ideal context for studying the matter.

“No one else wears this shirt on my watch. No one”

A 2013 paper by Parks et al examined around 800 such incidents of what was deemed to be verbal or physical aggression to determine what kinds of conflicts arose, what types people tends to get involved in them, and how they became involved. As an initial note – and this will become relevant shortly – aggression was defined in a particular way that I find to be troublesome: specifically, there was physical aggression (like hitting or pushing), verbal aggression (like insults), and unwanted or persistent sexual overtures. The problem here is that though failed or crude attempts at flirting might be unwanted, they are by no means aggressive in the same sense that hitting someone is, so aggression might have been defined too broadly here. That said, the “aggressive” acts were coded for severity and intent, third-party intervention was coded as present or absent and, when present, whether it was an aggressive or non-aggressive intervention, and all interactions were coded for the sex of the parties and their level of intoxication.

The first question is obviously how often did third parties become involved in an aggressive encounter? The answer is around a third of the time on average, so third-party involvement in disputes is by no means an infrequent occurrence. Around 80% of the third parties that intervened were also male. Further, when third parties did become involved, they were about twice as likely to become involved in an non-aggressive fashion, relative to an aggressive one (so they were more often trying to diffuse the situation, rather than escalating it). Perhaps unsurprising in the fact that most disputes tended to be initiated by people who appeared to be relatively more intoxicated, and the aggressive third parties tended to be drunker than the non-aggressive ones. So, as is well known, being drunk tended to lead to people being more aggressive, whether it came to initiating conflicts or joining them. Third parties also tended to become more likely to get involved in disputes as the severity of the disputes rose: minor insults might not lead to much involvement on the parts of others, while throwing a punch or pulling out a knife will. This also meant that mutually-aggressive encounters – ones that are likely to escalate – tended to draw more third-party involvement that one-sided aggression.

Of note is that the degree of third party involvement did fluctuate markedly: the disputes that drew the most third-party involvement were the male-on-male mutually-aggressive encounters. In those cases, third parties got involved around 70% of the time; more than double the average involvement level. By contrast, male-on-female aggression drew the least amount of third-party intervention; only around 17% of the time. This is, at first, a very surprising finding, given that women tend to receive lighter sentences for similar crimes, and violence against women appears to be less condoned than violence against men. So why would women garner less support when men are aggressing against them? Well, likely because unwanted sexual attention falls under the umbrella term of aggression in this study. Because “aggressive” does not equate to “violent” in the paper, all of the mixed-sex instances of “aggression” need to be interpreted quite cautiously. The authors note as much, wondering if male-on-female aggression generated less third-party involvement because it was perceived as being less severe. I think that speculation is on the right track, but I would take it further: most of the mixed-sex “aggression” might have not been aggressive at all. By contrast, when it was female-female mutual aggression (less likely to be sexual in nature, likely involving a fight or the threat of one), third parties intervened around 60% of the time. In other words, people were perfectly happy to intervene on behalf of either sex, so long as the situation was deemed to be dangerous.

“It’s only one bottle; let’s not be too hasty to get involved yet…”

Another important caveat to this research is that the relationship of the third parties that became involved to the initial aggressors was not known. That is, there was no differentiation between a friend or a stranger coming to someone’s aid when aggression broke out. If I had to venture a guess – and this is probably a safe one – I would assume that most of the third parties likely had some kind of a relationship to the people in the initial dispute. I would also guess that non-violent involvement (diffusing the situation) would be more common when the third parties had some relationship to both of the people involved in the initial dispute, relative to when it was their friend against a stranger. I happen to feel that the relationship between the parties who become involved in these disputes has some rather large implications for understanding morality more generally but, since that data isn’t available, I won’t speculate too much more about it here. What I will say is that the focus on how strangers behave towards one another in the lab – as is standard for most research on moral condemnation – is likely missing a large part of how morality works, just like how experimental demand characteristics seemed to make people look more altruistic than they are in naturalistic settings. Getting friends together for research poses all sorts of logistically issues, but it is a valuable source of information to start considering.

 References: Parks, M., Osgood, D., Felson, R., Wells, S., & Graham, K., (2013). Third party involvement in barroom conflicts. Aggressive Behavior, 39, 257-268.

Classic Theory In Evolution: The Big Four Questions

Explanations for things appear to be a truly vexing issue for people in many instances. Admittedly, that might sound a little strange; after all, we seem to explain things all the times without much apparent effort. We could consider a number of examples for explanations of behavior: people punch walls because they’re angry; people have sex because it feels good; people eat certain foods because they prefer those flavors, and so on. Explanations like these seem to come automatically to us; one might even say naturally. The trouble that people appear to have with explanations is with respect to the following issue: there are multiple, distinct, and complimentary ways of explaining the same thing. Now by that I don’t mean that, for instance, someone punched a wall because they were angry and drunk, but rather that there are qualitatively different ways to explain the same thing. For instance, if you ask me what an object is, I could tell you it’s a metallic box that appears to run on electricity and contains a heating element that can be adjusted via knobs; I could also tell you it’s a toaster. The former explanation tells you about various features of the object, while the latter tells you (roughly) what it functions to do (or, at least, what it was initially designed to do).

…And might have saved you that trip to the ER.

More precisely, the two issues people seem to run into when it comes to these different kinds of explanations is that they (a) don’t view these explanations as complimentary, but rather as mutually-exclusive, or (b) don’t realize that there are distinct classes of explanations that require different considerations from one another. It is on the second point that I want to focus today. Let’s start by considering the questions found in the first paragraph in what is perhaps their most basic form: “what causes that behavior?” or, alternatively, “what preceding events contributed to the occurrence of the behavior?” We could use as our example the man punching the wall to guide us through the different classes of explanations, of which there are 4 generally-agreed upon categories (Tinbergen, 1963).

The first two of these classes of explanations can be considered proximate – or immediate – causes of the behavior. The standard explanation many people might give for why the man punched the wall would be to reference the aforementioned anger. This would correspond to Tinbergen’s (1963) category of causation which, roughly, can be captured by considerations of how the cognitive systems which are responsible for generating the emotional outputs of anger and corresponding wall-punching work on a mechanical level: what inputs do they use, how are these inputs operated upon to generate outputs, what outputs are generated, what structures in the brain become activated, and so on. It is on this proximate level of causation that most psychological research focuses, and with good reason: the hypothesized proximate causes for behaviors are generally the most open to direct observation. Now that’s certainly not to say that they are easy to observe and distinguish in practice (as we need to determine what cognitive or behavioral units we’re talking about, and how they might be distinct from others), but the potential is there.

The second type of explanation one might offer is also a proximate-type of explanation: an ontological explanation. Ontology refers to changes to the underlying proximate mechanisms that takes place during the course of development, growth, and aging of an organism. Tinbergen (1963) is explicit in what this does not refer to: behavioral changes that correspond to environmental changes. For instance, a predator might evidence feeding behavior in the presence of prey, but not evidence that behavior in absence of prey. This is not good evidence that anything has changed in the underlying mechanisms that generate the behavior in question; it’s more likely that they exist in the form they did moments prior, but now have been provided with novel inputs. More specifically, then, ontology refers, roughly, to considerations of what internal or external inputs are responsible for shaping the underlying mechanisms as they develop (i.e. how is the mechanism shaped as you grow from a single cell into an adult organism). For instance, if you raise certain organisms in total darkness, parts of their eyes may fail to process visual information later in life; light, then, is a necessary developmental input for portions of the visual system. To continue on with the wall-punching example, ontological explanations for why the man punched the wall would reference what inputs are responsible for the development of the underlying mechanisms that would produce the eventual behavior.

Like their father’s fear of commitment…

The next two classes of explanations refer to ultimate – or distal – causal explanations. The first of these is what Tinbergen calls evolution, though it could be more accurately referred to as a phylogenetic explanation. Species tend to resemble each other to varying degrees because of shared ancestry. Accordingly, the presence of certain traits and mechanisms can be explained by homology (common descent). The more recently two species diverged from one another in their evolutionary history, the more traits we might expect the two to share in common. In other words, all the great apes might have eyes because they all share a common ancestor who had eyes, rather than because they all independently evolved the trait. Continuing on with our example, the act of wall-punching might be explained phylogenetically by noting that the cognitive mechanisms we possess related to, say, aggression, are to some degree shared with a variety of species.

Finally, this brings us to my personal favorite: survival value. Survival value explanations for traits involve (necessarily-speculative, but perfectly testable) considerations about what evolutionary function a given trait might have (i.e. what reproductively-relevant problem, if any, is “solved” by the mechanism in question). Considerations of function help inform some of the “why” questions of the proximate levels, such as “why are these particular inputs used by the mechanism?”, “why do these mechanisms generate the output they do?”, or “why does this trait develop in the manner that it does?”. To return to the punching example, we might say that the man punched the wall because aggressive responses to particular frustrations might have solved some adaptive problem (like convincing others to give you a needed resource rather than face the costs of your aggression). Considerations of function also manage to inform the evolution, or phylogeny, level, allowing us to answer questions along the lines of, “why was this trait maintained in certain species but not others?”. As another for instance, even if cave-dwelling and non-cave dwelling species share a common ancestor that had working eyes, that’s no guarantee that functional eyes will persist in both populations. Homology might explain why the cave-dweller develops non-functional eyes, but it would not itself explain why those eyes don’t work. Similarly, noting that people punch walls when they are angry alone does not explain why we do so.

All four types of explanations answer the question “what causes this behavior?”, but in distinct ways. This distinction between questions of function and questions of causation, ontogeny, and phylogeny, for instance, can be summed up quite well by a quote from Tinbergen (1963):

No physiologist applying the term “eye” to a vertebrate lens eye as well as a compound Arthropod eye is in danger of assuming that the mechanism of the two is the same; he just knows that the word “eye” characterizes achievement, and nothing more.

Using the word “eye” to refer to a functional outcome of a mechanism (processing particular classes of light-related information) allows us to speak of the “eyes” of different species, despite them making use of different proximate mechanisms and cues, developing in unique fashions over the span of an organism’s life, and having distinct evolutionary histories. If the functional level of analysis was not distinct, in some sense, from analyzes concerning development, proximate functioning, and evolutionary history, then we would not be able to even discuss these different types of “eyes” as being types of the same underlying thing; we would fail to recognize a rather useful similarity.

“I’m going to need about 10,000 contact lens”

To get a complete (for lack of a better word) understanding of a trait, all four of these questions need to be considered jointly. Thankfully, each level of analysis can, in some ways, help inform the other levels: understanding the ultimate function of a trait can help inform research into how that trait functions proximately; homologous traits might well serve similar functions in different species; what variables a trait is sensitive towards during development might inform us as to its function, and so on. That said, each of these levels of analysis remains distinct, and one can potentially speculate about the function of a trait without knowing much about how it develops, just as one could research the proximate mechanisms of a trait without knowing much about its evolutionary history.

Unfortunately, there has been and, sadly, continues to be, some hostility and misunderstandings with respect to certain levels of analyzes. Tinbergen (1963) had this to say:

It was a reaction against the habit of making uncritical guesses about the survival value, the function, of life processes and structures. This reaction, of course healthy in itself, did not (as one might expect) result in an attempt to improve methods of studying survival value; rather it deteriorated into lack of interest in the problem – one of the most deplorable things that can happen in science. Worse, it even developed into an attitude of intolerance: even wondering about survival value was consider unscientific

That these same kinds of criticisms continue to exist over 50 years later (and they weren’t novel when Tinbergen was writing either) might suggest that some deeper, psychological issue exists surrounding our understanding of explanations. Ironically enough, the proximate functioning of the mechanisms that generate these criticisms might even give us some insight into their ultimate function. Then again, we don’t want to just end up telling stories and making assumptions about why traits work, do we?

References: Tinbergen, N. (1963). On aims and methods of Ethology. Zeitschrift für Tierpsychologie, 20, 410-433.

Should Evolutionary Psychology Be A History Course?

Imagine for a moment that you happen to live in a Dr. Seuss-style world. Having just graduated from your local institute of educational hobnobbery, you find yourself hired into a lucrative new position: you’re a whatsitdoer. The job description is self-explanatory: it’s your job to examine a series of curious-looking objects and figure out what it is they were designed to do; what their function happens to be. On your first day at work, a shiny metal box comes down the conveyer belt. You begin to examine the object for evidence of special design. That is, does the object appear to be improbably well-designed for a solving various aspects of a particular task with efficiency? You note that the black cord ending in metal prongs running out of the box might suggest that it runs on electricity, the two slots at the top of the box appear to be shaped appropriately so as it fit bread rather well, and there appears to be a heating apparatus within the box. You test each design feature according: the device only functions when plugged it, bread does indeed fit well in the box, and is evenly toasted by the heating element. Importantly, larger items don’t seem to fit in well, smaller items fall in, becoming unreachable, and non-bread items, like CDs tend to melt or catch fire. In other words, the function of this tool appears as if it were designed to use a relatively narrow set of inputs to produce a useful output – toast.

Alternative hypothesis 34: Bath warmer

When you report the results of your tests to your boss, however, he’s not at all pleased with you analysis: “How can you possibly say that this object is designed to make toast when you haven’t recreated the steps of its manufacturing process? Until you have examined the history of how this object has come to be, how the material it is made out of was gathered and shaped, as well as what earlier prototypes of the model might have looked like extending back thousands of years, I can’t accept your suggestion, as you haven’t tested your functional explanation at all!” Now this all strikes you as very strange: you haven’t made any claims about how the object was developed or what earlier versions looked like; you made a claim about how the contemporary object you were given likely functions. As such, understanding the history of the object, while perhaps a neat piece of information that might inform later research on function, is not by any means a requirement for understanding an object’s function. In other words, you should be able to persuade your boss that the toaster is pretty good at making toast without having to give him a complete history of the thing.

Sure; it’s possible that the toaster-like object actually wasn’t designed to make toast at all; toast just happens to be a pretty convenient byproduct of another function it was designed to carry out. However, if we were deriving predictions about what that alternative function was, we still shouldn’t need the history lesson to do that. It’s not that the history information would be necessarily useless: for instance, if you knew the device existed before bread was a thing, then toasting bread certainly couldn’t have been its initial function (though it may well have been co-opted for that function when bread – or pop tarts – became a thing). However, if toasters are well-suited for other functions, you should be able to demonstrate those other functions with design evidence.  History is useful insomuch as it helps inform us about what design evidence to look for, certainly, but does not itself inform us as to functionality.

That said, there have been suggestions that phylogenetic analyzes (examinations of the branching of evolutionary tree) can help inform us as to whether a trait is functional (i.e. an adaptation) or not. Specifically, Fraley, Brumbaugh, & Marks (2005) wrote that, “In order to evaluate the adaptive nature of the relationship between traits, it is necessary to account for phylogenetic relationships among species” (p.733, emphasis mine). The authors go on to note, correctly, that species may be similar to one another because of a shared evolutionary history: rather than all the ape species evolving eyes independently, a common ancestor to all of them might well have had eyes and, because we share that ancestor, we all have eyes as well. Now, as you should be careful to note, this is a claim about the evolutionary history of the trait: whether it was independently evolved multiple times in different lineages, or whether it was evolved once and then maintained into subsequent generations. You should note, however, that this is not a functional claim: it doesn’t tell us what eyes do, what inputs they use, what outputs they generate, and so on. Some examples should make this distinction quite clear.

Figure 1: This ugly bird

Let’s consider, as an example, two species of birds: the ostrich and any variety of parrot you’d prefer. In the interests of full disclosure, I don’t know how recently the two species shared a common ancestor, but at some point we can say they did. Further, for the sake of argument, let’s say that this common ancestor between ostriches and parrots had feathers. The fact that both ostriches and parrots have feathers, then, can be said to be the result of homology (i.e. shared ancestry). However, this does not tell us anything about what the function(s) of these feathers are in their respective species, nor what selective pressures are responsible for their initial appear or maintenance across time. For instance, parrots are capable of flight while ostriches are not. We might expect that parrot feathers show some adaptations for that function, whereas such adaptive designs might have been degraded or lost entirely in ostriches (presuming the common ancestor flew, that is). However, the feathers might also serve other, identical functions in both species: perhaps feathers are also used to keep both species warm, or are advertised during sexual displays. Whatever the respective functions (or lack thereof) of these feathers in different species, we are unable to deduce that function from a phylogenetic analysis alone. What we need are considerations of what adaptive tasks the feathers might serve, and what design evidence we might expect to find because of that.

Fraley et al (2005) go on to suggest that if two traits repeatedly evolve together across species, these, “…correlation[s] between the traits…strongly suggests a functional relationship” (p. 734, emphasis mine). Again, the claim being made is that we can go from history – the two traits tend to show up together – to function. On top of the problems outlined above, such a statement runs into another large obstacle: non-functional or maladaptive byproducts of traits should be expected to correlate as well as adaptive ones. Let’s start with a non-functional example: imagine that placental mammals evolved multiple times over the course of history. If you were examining many different species, you’d probably see a good correlation between the evolution of placentas and presence of belly-buttons. However, the correlation between these two traits doesn’t tell you anything at all about the function (or lack thereof) of either placentas or belly-buttons. In another case, you might notice that there’s a pretty decent correlation between animals with a taste for sugar and the development of cavities in their teeth, but this in no way implies that a preference for sugar has any functional relationship with cavities; bacteria dissolving your teeth generally has poor fitness outcomes, and wouldn’t be selected for.

One final example might help make the point crystal clear: human male investment in children. Let’s say you have two males displaying the same behavior: buying food for their child. That’s awfully charitable of them. However, in one case, the man is the genetic father of the child, whereas the other male is only the child’s stepfather. These behaviors, while ostensible similar, might actually be serving distinct functions. In the case of the genetic father, the investment in that child might involve mechanisms designed for kin-directed altruism (i.e. investing in the child because the child carries some of his genes) and/or mechanisms designed for mating effort (i.e. investing in the child as a means of increasing sexual access to the mother). In contrast, we might expect the stepfather to be investing for the latter reason, but not the former. In other words, we have the same behavior – investing in children – being driven by two very different functional mechanisms. The predictions that can be drawn from these alternative functions are testable even without any reference at all to history or phylogeny: as it turns out, genetic fathers living with the mother invest more than genetic fathers not living with the mother, but genetic fathers continue to invest in offspring even lacking the relationship. On the other hand, stepfathers will invest in children when living with the mother, but when the relationship ends their investment tends to all but dry up entirely. Further, when both are living with the mother, genetic fathers invest more than stepfathers (Anderson, Kaplan, & Lancaster, 1999). This evidence is consistent with a role for both mechanisms designed for investing in children for inclusive fitness and mating reasons. Despite the surface level similarities, then, the investment of these two males might actually be being driven by different functional considerations.

And we didn’t even need a fossil record to figure that out.

So, when it comes to testing claims of biological function, there is no necessity for information about phylogeny: you don’t need to know where traits originated or what earlier versions of the trait were like in order to test competing hypotheses. That’s not to say that such information might not be useful: if you didn’t know about bread, you might have a more difficult time understanding some of the toaster’s design, just as if you didn’t know about toasters you might be hard pressed to explain the shape of pop-tarts (or their name, for that matter). Similarly, correlations between traits do not “strongly suggest” any evidence of a functional relationship either; some correlations might be consistent with a particular functional relationship, sure, but the correlation itself tells you comparatively little when compared with evidence of function (just like correlations between ice cream sales and murder do not strongly suggest any causal relationship, though an experiment examining whether feeding people ice cream made them more violent might). Claims about function should be kept distinct from claims about history. Why the two seem to get conflated from time to time is certainly an interesting matter.

References: Anderson, K., Kaplan, H., & Lancaster, J. (1999). Parental care by genetic fathers and stepfathers I: Reports from Albuquerque men. Evolution and Human Behavior, 20, 405-431.

Fraley, R., Brumbaugh, C., & Marks, M. (2005). The evolution and function of adult attachment: A comparative and phylogenetic analysis. Journal of Personality and Social Psychology, 89, 731-746.