Monthly Archives: May 2012

Red Herrings And Moral Wiggle Room

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I don’t know whether it was actually J.K. Rowling who wrote/said that, but as a shallow, vain, and boring person who also happens to be in great shape, this quote really speaks to me; no doubt it also speaks to the deeper, selfless, and interesting portion of the population who read the quote surrounded by stacks of old pizza boxes and empty cartons of Ben and Jerry’s, but I get the sense it speaks to us in different ways (I also get the sense my keyboard is substantially less sticky).

Whoever is being quoted would appear to be implying something like the following: “Someone might be unhealthy/unattractive, but they could be X instead, which is worse. Therefore, being fat is OK”.  The logical shortcomings of that implication are so vast that the author has either never taken a philosophy class or has a PhD in the subject. I’d doubt Rowling’s(?) commitment to that line of thought in any case, simply by pointing out the actors in the Harry Potter films are less than fat – far less so than the population at large – meaning plenty of good actors probably got passed over because they were fat. More importantly, the entire quote is a red herring; a statement intended to distract attention away from the matter at hand.

Consider an alternative, but similar statement: Is a little thievery the worst thing someone can do? Is it worse than murder, rape, or physical assault? Not to me. The problem should become apparent here very quickly; whether or not Y is worse than X should have no bearing on the status of X. Whatever X is, it needs to be able to stand on its own feet. There is one case where there is an exception, and that’s concerning a certain parking ticket issued to me. Parking police, go fight some real crime. There are bigger concerns out there than whether I probably accidentally parked in a handicapped spot for a few hours. I already had to get my car out of impound; isn’t that enough for you people? It’s not like I was drunk driving. Or fat.

So  what does this quote tell us about how human psychology functions? One potential lesson we could take from it is that people are bad at justifying things coherently (see my last post, and probably future ones). Of greater interest, however, is the fact that people are interested in justifying their behavior as intensely as they are.

I remember seeing a commercial for yogurt on TV not so long ago that made fun of this bit of peculiar psychology. A woman is seen standing in front of a fridge, eying some cake. She thinks to herself that she could eat some celery and the cake, and somehow the celery would cancel the cake out. Women; am-i-right fellas? She wants to eat that cake and is trying to justify doing so to herself. There are two things to say about that: first, it’s great evidence for modularity of the mind, as if anymore was needed. Second, what good could those justifications possibly be? (They certainly don’t work out all the time)

To start at answering that question, let’s examine some research by Larson and Capra (2009) on the subject of what’s called “Moral Wiggle Room”. The research involved a dictator game; it’s a classic economic research design in which one player is designated the “dictator” and another player is designated to lie there and take it…. I mean, the “receiver”. The dictator is given a sum of money, say $10, and the ability to decide how the money is to be divided. Whatever the dictator decides is what goes, so if the dictator wants to keep $9 and give $1 to the receiver, so be it. Not only is it a neat way to examine certain aspects of our psychology, but it’s also an effective way of disappointing people in the name of science. Talk about killing two birds with one stone.

Research on Moral Wiggle Room goes (basically) as follows: In one group, the dictators need to decide between a higher payoff for themselves and a lower payoff for someone else, or a lower payoff for themselves that gives the receiver more money (A $6/$1 option or a $5/$5 option), or between payoffs that benefit both parties ($6/$5 option or a $5/$1 option). Another group of dictator’s payments look like the following: $6/$? or $5/$? While these dictators don’t know up front what the receiver will get, they can find out for free. With the click of a button, they can reveal the payoffs; it costs nothing in terms of time or money to find out. So what do people do?

In the first group, where payments are known, about 75% of dictators choose the fair option, so maybe life in the Soviet Union really wasn’t that bad. What happens when dictators are given the choice to not know how their actions will affect others? Slightly more than half of them choose to remain ignorant and not reveal the payoffs; of that 50%, who didn’t reveal, 100% took the higher offer. (The ones who revealed weren’t exactly saints either, since over half took the higher payment at the expense of the receiver)

Why might people not want to know how their actions effect others, even when it costs nothing to know? For starters, being strategically ignorant can only help them in terms of payoff: best case scenario, they find out the option that’s better for them is better for someone else as well  and they take it anyway; worst case, they now have access to information that opens possibilities for creating expectations of certain treatment in which their wallets are now a slightly lighter (in theory anyway. While these games are played anonymously, we’re all still sitting here judging their actions to ourselves, demonstrating the point). However, by remaining ignorant, they can also honestly claim they didn’t know they were making someone worse off. This could allow them to benefit indirectly (they may be able to better persuade others that they’re morally upstanding citizens or avoid punishment for their actions more effectively, should they come to light, without needing to lie about it) in addition to the direct benefits (they made more money).

Of course, these games are played at low-stakes, information is free, easy to obtain, and unambiguous, while decisions are made anonymously. One could think of how the results could change when any of those factors do. While things can get messy quickly, there are clearly cases in which the reasons for not knowing are better than knowing for some. My guess is that those reasons center around persuasion through justification, specifically being able to convince people that what you did was OK because you didn’t know how other people would feel. While that argument happens to be a red herring in the case of the research reviewed here – they could have found out if they wanted – we should not forget that red herrings are used as often as they are because they have a habit of working. And by working, I mean they can help make people forget you’re full of shit because they’re looking somewhere else.

References: Larson, T. & Capra, C. M. (2009). Exploiting moral wiggle room: illusory preference for fairness? A comment. Judgment and Decision Making, 4, 467-474.

I Read It, So It Must Be True

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The first principle [in science] is that you must not fool yourself, and you are the easiest person to fool – Richard Feynman

It feels nice to start a post with a quote from some famous guy; it just makes the whole thing that much more official. I decided to break from my proud, two-note, tradition and write about some psychology that doesn’t have to do with gay sex, much to the disappointment of myself and my hordes of dedicated fans. Instead, today I’ll be examining the standards of evidence with which claims are evaluated.

Were we all surveyed, the majority of us would report that we’re – without a doubt – in at least the top half of the population in terms of intelligence, morality, and penis size. We’d also probably report that we’re relatively free from bias in our examination of evidence, relative to our peers; the unwashed masses of the world, sheep that they are, lack the critical thinking abilities we do. Were we shown the results of research that said the majority of people surveyed also consider themselves remarkably free of bias, relative to the rest of the world – a statistical impossibility – we’d shake our head at how blind other people can be to their own biases, all the while assuring the researcher that we really are that good.

I think you see where I’m going with this, since most everyone is above average in their reasoning abilities.

In some (most?) cases when evidence isn’t present, it’s simply assumed to exist. If I asked you whether making birth control pills more available would increase or decrease the happiness of women, on average, I’d guess you would probably have an answer for me that didn’t include the phrase “I don’t know”. How do you suppose you’d respond if you read about some research evidence that contradicted your answer about it?

In real life, evidence is a tricky thing. Results from almost any source can be tainted from any number of known and unknown factors. Publication bias alone can lead to positive results being published more often than null results, leading to an increase in the number of false positives, not to mention other statistical sleights of hand that won’t be dealt with here. The way questions are asked can lead respondents towards giving certain answers. Sometimes the researchers think they’re measuring something they aren’t. Sometimes they’re asking the wrong questions. Sometimes they’re only asking certain groups of people who differ in important ways from other people. Sometimes (often) the answers people give to questions don’t correspond well to actual behavior. There are countless possible flaws, uncontrolled variables, and noise that can throw a result off.

Here’s the good news: people are pretty alright at picking out those issues (and I do stress alright; I’m not sure I’d call them good at it). Here’s the bad news: people are also substantially worse at doing it when the information agrees with what they already think.

Two papers examined this tendency: Lord, Ross, & Lepper (1979) and Koehler (1993). In the first, subjects were surveyed about their views regarding the death penalty and were categorized as those who were either strongly in favor of it or strongly opposed. The subjects were then given a hypothetical research project and its results to evaluate; results that either supported the usefulness of the death penalty in reducing crime or opposing its usefulness. Following this, they were then given another study that came to the opposite conclusion. So here we have people with very strong views being given ambiguous evidence. Surely, seeing the evidence was mixed, people would begin to mellow in their views, perhaps compromising to simply breaking a thief’s hands over killing him or letting him escape unharmed, right?

Well, the short answer is “no”; the somewhat longer answer is “nooooooo”. When subjects rated the research they were presented with, they pointed out the possible ways that the research opposing their views could have been misconducted and why the results aren’t valid to their satisfaction. However, they found no corresponding problems with the results that supported their views, or at least no problems really worth worrying about. Bear in mind, they read this evidence back to back. Their views on the subject, both pro and con, remained unchanged; if anything, they became slightly more polarized than they already were at the beginning.

Koehler (1993) found a similar result: when graduate students were evaluating hypothetical research projects, those research projects that found results consistent with the student’s beliefs were rated more favorably than those with opposing results. We’re not just talking unwashed masses anymore; we’re talking about unwashed and opinionated graduate students. There was also an interaction effect: specifically, the stronger the preexisting belief, the more favorably agreeing studies were rated. A second study replicated this effect using a population of skeptics and paranormal researchers examining evidence for ESP (if you’re curious, the biases of the paranormal researchers seemed somewhat less pronounced. Are you still feeling smug about the biases of others, or are you feeling the results aren’t quite right?).

The pattern that emerges is that bias progressively creeps in as investment in a subject increases. We see high-profile examples of it all the time in politics: statistics are often cited that are flimsy at best and made up at worst. While we often chalk this up to politicians simply outright lying, the truth is probably that they legitimately believe what they are saying is true, but it could be something they accepted without even looking into it, or looking into the matter with a somewhat relaxed critical view.

And before we – with our statistically large penises and massive intellect – get all high and mighty about how all politicians are corrupt liars, we’d do well to remember the research I just talked about didn’t focus on politicians. The real difference between non-politicians and official politicians is that the decisions of the latter group tend to carry consequences and are often the center of public attention. You’re probably no different; you’re just not being recorded and watched by millions of people when you do it.

Recently, I had someone cite a statistic at me that the average lifespan of a transsexual was 23 years old. As far as I can tell, the source of that statistic is that someone said it once, and it was repeated. I’m sure many people have heard some statistics about how many prostitutes are actually being coerced to work against their will; you might do well to consider this. Many are probably familiar with the statistic that women earn 75 cents to every dollar a man earns as a result of sexism and discrimination. Some of you will be pleased to know that discrepancy drops very sharply once you actually start to control for basic things, like number of hours worked, education, field of work, etc. Is some percentage of whatever gap remains due to sexism? Probably, but its far, far smaller than many would make it out to be; the mere existence of a gap is not direct evidence of sexism.

Not only are unreliable statistics like those parroted back by people who want to believe (or disbelieve) them for one reason or another, but the interpretations of those statistics are open to the same problem. I’m sure we can all think of times other people made this mistake, but I’ll bet most of us would struggle to think of times we did it ourselves, smart and good looking as we all are.

References: Koehler, J.J. (1993). The Influence of Prior Beliefs on Scientific Judgments of Evidence Quality. Organizational Behavior and Human Decision Processes, 56, 28-55.

Lord, C.G., Ross, L., & Lepper, M.R. (1979). Biased Assimilation and Attitude Polarization: The Effects of Prior Theories on Subsequently Considered Evidence. Journal of Personality and Social Psychology, 37, 2098-2109.

OKCupid Blog: Gay Vs. Straight Sex

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I’m of the mindset that gay men and women are pretty much just like straight men and women, the real difference being their preference for which gender they find attractive, which is why the following presentation struck me as interesting:

Their sample size was 3.2 million, which is pretty fucking impressive. The thought of having access to the data set they do is sexually thrilling for me (perhaps we could tack another letter onto the end of LBGT for people with my proclivities), so I decided to do another edition of Pop Psychology to take a closer look at what our Okcupid blogger decided to present from that data set and raise some questions that will remain unanswered, but serve as practice (for me, anyway) for critical evaluation. After all, having access to something so amazing demands that it not be squandered or misused.

The first question I’d pose is about that impressive sample size itself: what percentage of it represents straight/ gay men and women? You’d think, this being an article about straight vs. gay sex, that would be the first thing they’d mention. If we assume population level frequencies, that would mean that sample is about 1.6 million men and women total, about 80,000 of which will be gay men (5%, published range from 3-10%) and about 40,000 of which will be lesbian women (2.5%, published range from 1 – 3%). That is assuming we can assume population levels; there is no data presented concerning the the percentage of Okcupid users who identify as straight or gay in the first place. I’m sure the Okcupid people have this data available, but it’s not shown here for whatever reason. Since it’s not shown, there’s no way of inferring whether this population is representative or not, which could throw a possible wrench into its interpretation. I’m not saying it does, just that it might.

Let’s start by looking at the first point raised by the article:

Gay people are not sexually interested in straights.    

Match Search Returns

  • only 0.6% of gay men have ever searched for straight matches.
  • only 0.1% of lesbians have ever searched for straight matches.

What that tells us is that most gay and lesbian people do not go looking explicitly for straight people on the website, which is pretty expected, especially when people’s sexual orientations are readily visible. What that does not tell us is is that gay people are not sexually interested in straight people; I assume most of them are, and I assume that for the same reason that most heterosexual men are sexually interested in lesbians, even though they’ll probably never sleep with them (but more on that in a bit). I have found that knowing a woman’s sexual orientation has not made me any more or less attracted to them, though it does affect my judgments of whether or not I’m likely to have sex with them. I imagine other people don’t need to know someone’s sexual orientation before they feel any sexual attraction, nor do I feel that knowledge would do much to change that attraction. The website just allows for screening based on sexual orientation, skipping what would be an in-person trial and error process, since not everyone has their sexual orientation tattooed on their forehead.

Those absolute percentages are very small, granted, but they also tell us something else: relatively, gay men are six-times as likely to have ever searched for straight men than lesbians are to have searched for straight women; an interesting finding to be sure. Bear in mind those numbers refer to people who have ever searched for a straight match, not how frequently they do it. My guess is that gay men also search for straight matches more frequently, but without the data available I can’t say with any certainty. Moving on:

Gay people aren’t promiscuous.

Median Reported Sex Partners

  • straight men: 6
  • gay men: 6
  • straight women: 6
  • gay women: 6

This stuck out to me above everything else in the article because it stands in stark contrast to everything I’ve ever read in the published literature. Simply put, men and women (straight ones) don’t report identical numbers of sexual partners, generally speaking, and men and women (gay ones) don’t report identical numbers of sexual partners. Has Okcupid, with its huge data set just blown all those other results out of the water? I don’t think so; consider the following number sets to understand why:

(1) 0, 0, 1, 3, 5, 6, 10, 30, 100
(2) 3, 3, 3, 3, 5, 7, 7, 7, 7

If we assume those numbers represent number of sexual partners, then in both samples, the median (the middle) number of partners is 5; the mean (the average) number of partners is still 5 for sample (2), but in (1) it’s 17.22. See the very big difference? Most every study I recall reading reports the mean, and if they report the median at all, it’s in conjunction with the mean. That the Okcupid post only reports the median at best doesn’t allow them to make the statement they did, and at the worst reeks of spin to attempt to make groups look  more similar than they actually are.

There are two other problems: the first is that those numbers refer to number of partners, not number of same/opposite sex partners. It’s not uncommon for lesbians to have several male partners (in some cases, more male partners than female ones), and that can matter a lot (especially because the same isn’t true of gay men).
The second problem, again, returns to the sample itself: the age of these people are not reported. Older people tend to have more sexual partners than younger ones, simply because they’ve had more time to rack up the numbers. Gay men tend to report establishing a clear sense of their orientation before lesbians, which could mean our lesbian sample is substantially older. Perhaps they controlled for this, but if they did, they make no mention of it (they do mention controlling for things in other blog posts, so I can only assume they did not here).

  • 45% of gay people have had 5 or fewer partners (vs. 44% for straights)
  • 98% of gay people have had 20 or fewer partners (vs. 99% for straights)

What is curious about this is that the previous stats had broken down the data by gender and sexual orientation; here, we see it recombined to just sexual orientation. I can’t think of any good reason to do that from a strictly informative point of view, which implies to me there’s probably something else going on (namely, controlling the light in which these findings are presented).
While those differences in percentages appear small absolutely, as was the case previously, they can also be read to say something else: gay people are twice as likely to have more than 20 partners, relative to straight people. I also assume that effect is largely being carried by the male portion of the gay side, which could potentially mean that gay men are up to four-times as likely to have over 20 partners, depending on what percentage of that gay 2% and straight 1% are men. So gay men could be somewhere between 2-4 times as likely to have over 20 partners, relative to their straight counterparts, which strikes me as more promiscuous.On that note:

we found that just 2% of gay people have had 23% of the total reported gay sex, which is pretty crazy.

An interesting finding to sure, but the same probably holds for straight people. Male numbers of sexual partners (straight) are distributed differently from female numbers; there are a small number of men with a large number of sexual partners along with many men that have low numbers to no number at all. On the other hand, women are less likely to have the peaks that men do in the high end, but they’re also less likely to be shut out of the game entirely (fewer women with no numbers). Accordingly, if this was broken down by gender, I’d predict that most of that effect was being carried by gay men, not lesbians.

However, since we are dealing with a single gender in the case of gay men or women, the distribution curves would have to look different from their heterosexual counterparts: either the peaks of the gay community would have to be smaller than those of the straight community and the distribution more even, or larger numbers of gay men and women would not have (m)any sexual partners. Since we already know from the previously reported data that, at the upper end of 20+ partners, gays outnumber straights 2-to-1, that would require more gays not having, relative to straight people. That would mean, cutting off the top end of the distribution, the gay community should be even less promiscuous than the straight community, on average.

Then again, perhaps gay men are more promiscuous all around (which would simply shift the graph up), while lesbians are less so (shifting the graph down), but that article seems to imply that’s an unfair stereotype.

So there are good reasons to doubt the statement that promiscuity is equal across the four combinations of straight/gay men/women; it’s very expected, and established, the that groups are not the same sexually (men are not women, and women are not men). However, there are two more possibilities that the article doesn’t touch on that I think could underestimate the extent of gay promiscuity.

The first is the social risks openly gay people may face, which could result in them being less willing to try to hit on people they otherwise would like to. In that sense, it’s not that homosexuals are less promiscuous then they’d prefer by choice.

The second is the size of the dating/mating pool that gay men and women have to deal with; were only 2.5% of the population potentially sex-able to me (50% aren’t men, and of that 50% that are men, only about 5% are gay, and of that 5%, not all will be attractive), I’d either have to know many, many more people than average to reach the average number of sexual partners, or be particularly more motivated to make it happen, provided that 2.5% was no more promiscuous than the roughly 50% I have potentially available now. Since I don’t think gay people know substantially more people than straight ones, that raises the possibility of motivation and/or promiscuity.

Of course, none of this says anything about judging the worth of a person by their number or choice of sexual partners. I can’t help but wonder if the people at Okcupid were trying to present the data selectively to make the case that gay people are really just like straight people, which means they’re OK. If they were, they went wrong on two major fronts. The first is that the gay community does not need to be the same as straight people to be OK. They’re already OK; always have been. The second big issue is that for gay men and women to be similar to straight men and women, gay men are going to be different from lesbians along the same lines that straight men differ from straight women. The real differences in behavior emerge because when a man is pairing with other men, their sexual interests tend to converge more than the interests of men with women; that same goes for women pairing with other women. There’s no need for everyone to be identical for everyone to be equal, and trying to present select bits of the data to make them look more the same isn’t helping.