Savvy Shoppers Seeking Sex

There exists an idea in the economic field known as revealed preferences theory. People are often said to have preferences for this or that, but preferences are not the kind of thing that can be directly observed (just as much of our psychology cannot). As such, you need to find a way to infer information about these underlying preferences through something observable. In the case of revealed preferences, the general idea is that people’s decisions about what to buy and how much to spend are capable of revealing that information. For instance, if you would rather buy a Honda instead of a Ford for the same price, I have learned that your preferences – at least in the current moment – favor Hondas; if I were interested in determining the degree of that preference, I could see how much more you were willing to pay for the Honda. There are some criticisms of this approach – such as the the issue that people sometimes prefer A to B when compared to each other directly, but prefer B to A when presented with a third, irrelevant option – but the general principle behind it seems sound: people’s willingness to purchase goods and services positively correlates with their desires, despite some peculiarities. The more someone is willing to pay for something, the more valuable they perceive it to be.

“Marrying you is worth about $1,500 to me”

Now this is by no means groundbreaking information; it’s a facet of our psychology we are all already intimately familiar with. It does, however, yield an interesting method for examining people’s mating preferences when it’s turned on prostitution. In this case, a new paper by Sohn (2016) sought to examine how well men’s self-reported mating preferences for youthful partners were reflected in the prostitution market, where encounters are often short in duration, fairly anonymous, and people can seek out what they’re interested in, so long as they can afford it. It is worth mentioning at the outset that seeking youth per se is not exactly valuable in the adaptive sense of the word; instead, youth is valued (at least in humans) because of how it relates to both reproductive potential and fertility. Reproductive potential refers to how many expected years of future reproduction a woman has remaining before she reaches menopause and loses that capability. As such, this value is highest around the time she reaches menarche (signaling the onset of her reproductive ability) in her mid-teens and decreases over time until it reaches zero at menopause. Fertility, by contrast, refers to a woman’s likelihood of successful conception following intercourse, and tends to peak around her early twenties, being lower both prior to and after that point.

Since the type of intercourse sought by men visiting prostitutes is usually short-term in nature, we ought to expect the male preference for traits that cue high fertility to be revealed by the relative price they’re willing to pay for sex with women displaying them (since short-term encounters are typically aimed at immediate successful reproduction, rather than monopolizing a woman’s reproductive potential in the future). As such fertility cues tend to peak at the same ages as fertility itself, we would predict that women in their early twenties should command the highest price on the sexual market price, and this value should decline as women get older or younger. There are some issues with studying the subject matter, of course: sex with minors – much like prostitution in general – is often subject to social and legal sanctions. While the former issue cannot (and, really, should not) be skirted, the latter issue can be. One way of getting around the legal sanctions of prostitution in general is to study it in areas in the world where it is legal. In this instance, Sohn (2016) reports on a data set derived from approximately 8,600 prostitutes in Indonesia, ranging from ages 17-40, where, we are told, prostitution is quasi-legal.

The variable of interest in this data set concerns how much money the prostitutes received during their last act of commercial sex. This single-act method was employed in the hopes of minimizing any kinds of reporting inaccuracies that might come with trying to estimate how much money is being earned on average over long periods of time. While this choice necessarily limits the scope of the emerging picture concerning the price of sex, I believe it to be a justifiable one. Age was the primary predictor of this sex-related income, but a number of other variables were included in the analysis, such as frequency of condom use, years of schooling, age of first sex, and time selling sex. Overall, these predictor variables were able to account for over half of the variance in the price of sex, which is quite good.

“Priced to move!”

Supporting the hypothesis that men really do value these cues of fertility, the price of sex nominally rose from age 17 until it peaked at 21 (though this rise was not too appreciable), tracking fertility, rather than reproductive potential. Following that peak, the price of sex began to quickly and continuously decline through age 40, though the decline slowed passed 30. Descriptively, the price of sex at its minimum value was only about half the price of sex at peak fertility (which is a helpful tip for all you bargain-seekers out there…). Indeed, when age alone was considered, each additional year reduced the price of sex, on average, by about 4.5%; the size of that decrease uniquely attributable to age was reduced to about 2% per year when other factors were added into the equation, but both numbers tell the same story. A more detailed examination of this decrease grouped women into blocks of 5-year age periods. When considering age alone, there was no statistical difference between women in the 17-19 and 20-25 range. After that period, however, differences emerged: those in the 26-30 range earned 22% less, on average; a figure which fell to 42% less in the 30-34 group, and about 53% in the the 35-40 group.

This decrease in the price of sex over a woman’s lifespan is the opposite of how income usually works in non-sexual careers, where income rises with time and experience. It would be quite strange to work at a job where you saw your pay get cut by 2% each year you were with the company. It is likely for this reason that prostitutes in the 20-25 range were the most common (representing 32.6% of the sample), and those in older age groups were represented less heavily (27.6% in the 26-30 group, all the way down to 12% in the 35-40 range). When shopping for sex, then, men were not necessarily seeking the most experienced candidate for the position(s), but rather the most fertile one. As fertility declined, so too did the price. As price declined, women tended to leave the market. 

There were a few other findings of note, though the ‘whys’ explaining them are less straightforward. First, more educated prostitutes commanded a higher average asking price than their less educated peers, to the tune of about a 5% increase in price per extra year of school. As men and women both value intelligence highly in long-term partners, it is possible that cues of intelligence remain attractive, even in short-term contexts. Second, controlling for age, each year of selling sex tended to decrease the average price by about 1.5%. It is possible that the effects of prostitution visibly wear down the cues that men find appealing over time. Third, prostitutes who had ever used drugs or drank alcohol earned 12% more than their peers who abstained. Though I don’t know precisely why, it’s unlikely a coincidence that moral views about recreational drug use happen to be well predicted by views about the acceptability of casual sex (data from OKCupid, for instance, tells us the single best predictor of a woman’s interest in casual sex is whether she enjoys the taste of beer). Finally, prostitutes who proposed using condoms more often earned about 10% more than those who never did. I agree with Sohn’s (2016) assessment that this probably has to do with more desirable prostitutes being attractive enough to effectively bargain for condom use, whereas less attractive women compromise there in order to bring in clients. While men prefer sex without condoms, they appear willing to put that preference aside in the face of an attractive-enough prospect.  

“Disappointment now sold in bulk”

So what has been revealed about men’s preferences for sex with these data? Unfortunately, interpretation of prices is less straightforward than simply examining the raw numbers: their correspondence to other sources of data and theory should be considered. For instance, at least when seeking short term encounters, men seem to value fertility highly, and are willing to pay a premium to get it. This “real world” data accords well with the self-reports of men in survey and laboratory settings and, as such, seems to be easily interpretable. On other hand, men usually prefer sex without condoms, so the price premium among prostitutes who always suggest they be used would seem to, at face value, ‘reveal’ the wrong preference. Instead, it is more likely that prostitutes who already command a high price are capable of bargaining effectively for their use. In order to test such an explanation, you would need to pit the prospect of sex with the same prostitute with and without a condom against each other, both at the same price. Further, more educated prostitutes seemed to command a higher price on the sexual market: is this because men value intelligence in short-term encounters, educated women are more effective at bargaining, intelligence correlates with other cues of fertility or developmental stability (and thus attractiveness), or because of some other alternative? While one needs to step outside the raw pricing data obtained from these naturalistic observations to answer such questions effectively, the idea of using price data in general seems like a valuable method of analysis; whether it is more accurate, or a “truer” representation of our preferences than our responses to surveys is debatable but, thankfully, this need not be an either/or type of analysis.

References: Sohn, K. (2016). Men’s revealed preferences regarding women’s ages: Evidence from prostitution. Evolution & Human Behavior, DOI: 

Clues To The Function Of Moralistic Punishment

One of the major questions I’ve spent the better part of the last few years trying to work up an answer to is the matter of why – in the adaptive sense – people punish others as third parties moralistically. That is to ask why people condemn and punish others for engaging in behavior perceived to be “wrong”. This is not the same question as why people take revenge on others for their behavior; that kind of punishment isn’t terribly mysterious. Chimps, for instance, will punish those who cheated them, but they seem fairly uninterested in punishing those who cheated others (Riedl, Jensen, Call, & Tomasello, 2012). Humans are a bit different in that regard: not only do we involve ourselves in the disputes of others, but we do so on behalf of people who aren’t kin or even social allies. This is rather strange behavior, even though we do not usually perceive it to be so. I’m not the only one who has attempted an evolutionary explanation for moralistic punishment, of course; in my hubris, however, I do feel that the explanation I ended up floating tends to fit the existing data better than other, contemporary theories. Today, I wanted to try and demonstrate that fit by considering some relative-recent empirical research.

“I don’t know, man; I think it might be a little baggy. Try a size down”

The paper in question (Kurzban, DeScioli, & O’Brien, 2007) concerns audience effects on punishment. Specifically, it addresses the following question: do people punish others more (as third parties) when they are being watched and their decisions are being made public, relative to when they’re anonymous? The question was examined across two experiments. In the first of these, 43 participants viewed the outcome of a previous trust game in which one player had the choice between two different outcomes: $39 for himself and $1 for the other player, or $20 for both. In this case, the player had selected the former, selfish option. The participants in question were provided with $7 and told they could spend any amount of that money – from $0 to $7 – to deduct from the selfish player. For each dollar they spent on deductions, the selfish player would lose $3. Importantly, the participants were either doing so in conditions under which their spending would be unknown to anyone but themselves (n = 24), or conditions where the experimenter would known how much each particular participant spent (n = 19). In the anonymous condition, 38% of participants spent at least some money on punishment, whereas in the public condition, 47% opted to punish something. Importantly, however, the amount punished varied between these conditions. Those in the public condition tended to spend more on punishment than those in the anonymous condition when they did. For instance, though precise numbers are not reported, approximately 20% of the participants in the public condition paid the full $7 to punish the selfish player, as compared with 0% in the private condition.

The second experiment examined peoples’ responses to a different kind of economic game – a prisoner’s dilemma – where one player attempted to cooperate with their partner, but was met with defection. In terms of the outcome, this means that rather than both players getting $25 (if both had cooperated), the cooperative partner got $0 while the defector got $30. The participants in this experiment were shown this outcome and given $10. As before, the participants could spend any amount of this $10 to deduct from the defecting player at the 3-to-1 rate. In this case, the punishment decisions would either be known by (a) no one else but the participant (n = 31), (b) the experimenter alone (n = 26), or (c) the entire group of participants (n = 30). Again, fewer participants opted to punish at all when punishment was anonymous (42%) relative to when punishment was known to either the experimenter (65%) or the whole group (67%); the amount spent on punishment increased as well (Ms = $1.06, $2.54, and $3.17, respectively). Further, those in the public conditions also tended to display more anger, disgust, and contempt at the cheating, suggesting that they were more upset by the transgression when other people were watching (or they were at least pretending to be).

The existence of audiences seemed to have an important impact on determining moralistic punishment: not only did the presence of other people affect the percent of third parties willing to punish at all, but it also positively influenced how much they did punish. In a sentence, we could say that the presence of observers was being used as an input by the cognitive systems determining moralistic sentiments. While this may sound like a result that could have been derived without needing to run the experiments, the simplicity and predictability of these findings by no means makes them trivial on a theoretical level when it comes to answering the question, “what is the adaptive value of punishment?” Any theory seeking to explain morality in general – and moral punishment in particular – needs to be able to present a plausible explanation for why cues to anonymity (or lack thereof) are being used as inputs by our moral systems. What benefits arise from public punishment that fail to materialize in anonymous cases?

“If you’re good at something, never do it for free…or anonymously”

The first theoretical explanation for morality that these results cut against is the idea that our moral systems evolved to deliver benefits to other per se. One of the common forms of this argument is that our moral systems evolved because they delivered benefits to the wider group (in the form of maintaining beneficial cooperation between members) even if doing so was costly in terms of individual fitness. This argument clearly doesn’t work for explaining the present data, as the potential benefits that could be delivered to others by deterring cheating or selfishness do not (seem to) change contingent on anonymity, yet moral punishment does. 

These results also cut against some aspects of mutualistic theories for morality. This class of theory suggests that, broadly speaking, our moral sense responds primarily to behavior perceived to be costly to the punisher’s personal interests. In short, third parties do not punish perpetrators because they have any interest in the welfare of the victim, but rather because punishers can enforce their own interests through that punishment, however indirectly. To place that idea into a quick example, I might want to see a thief punished not because I care about the people he harmed, but rather because I don’t want to be stolen from and punishing the thief for their behavior reduces that probability for me. Since my interests in deterring certain behaviors do not change contingent on my anonymity, the mutualistic account might feel some degree of threat from the present data. As a rebuttal to that point, the mutualistic theories could make the argument that my punishment being made public would deter others from stealing from me to a greater extent than if they did not know I was the one responsible for punishing. “Because I punished theft in a case where it didn’t effect me,” the rebuttal goes, “this is a good indication I would certainly punish theft which did affect me. Conversely, if I fail to punish transgressions against others, I might not punish them when I’m the victim.” While that argument seems plausible at face value, it’s not bulletproof either. Just because I might fail to go out of my way to punish someone else who was, say, unfaithful in their relationship, that does not necessarily mean I would tolerate infidelity in my own. This rebuttal would require an appreciable correspondence between my willingness to punish those who transgress against others and those who do so against me. As much of the data I’ve seen suggests a weak-to-absent link in both humans and non-humans on that front, that argument might not hold much empirical water.

By contrast, the present evidence is perfectly consistent with the association-management explanation posited in my theory of morality. In brief, this theory suggests that our moral sense helps us navigate the social world, identifying good and bad targets of our limited social investment, and uses punishment to build and break relationships with them. Morality, essentially, is an ingratiation mechanism; it helps us make friends (or, alternatively, not alienate others). Under this perspective, the role of anonymity makes quite a bit of sense: if no one will know how much you punished, or whether you did at all, your ability to use punishment to manage your social associations is effectively compromised. Accordingly, third-party punishment drops off in a big way. On the other hand, when people will know about their punishment, participants become more willing to invest in it in the face of better estimated social return. This social return need not necessarily reside with the actual person being harmed, either (who, in this case, was not present); it can also come from other observers of punishment. The important part is that your value as an associate can be publicly demonstrated to others.

The first step isn’t to generate value; it’s to demonstrate it

The lines between these accounts can seem a bit fuzzy at times: good associates are often ones who share your values, providing some overlap between mutualistic and association accounts. Similarly, punishment, at least from the perspective of the punisher, is altruistic: they are suffering a cost to provide someone else with a benefit. This provides some overlap between the association and altruistic accounts as well. The important point for differentiating these accounts, then, is to look beyond their overlap into domains where they make different predictions in outcomes, or predict the same outcome will obtain, but for different reasons. I feel the results of the present research not only help do that (inconsistent with group selection accounts), but also present opportunities for future research directions as well (such as the search for whether punishment as a third party appreciably predicts revenge).

References: Kurzban, R., DeScioli, P., & O’Brien, E. (2007). Audience effects on moralistic punishment. Evolution & Human Behavior, 28, 75-84.

Riedl, K., Jensen, K., Call, J., & Tomasello, M. (2012). No third-party punishment in chimpanzees. Proceedings of the National Academy of Science, 109, 14824–14829

Exaggerating With Statistics (About Rape)

“As a professional psychology researcher, it’s my job to lie to the participants in my experiments so I can lie to others with statistics using their data”. -On understanding the role of deception in psychology research

In my last post, I discussed the topic of fear: specifically, how social and political agendas can distort the way people reason about statistics. The probable function of such distortions is to convince other people to accept a conclusion which is not exactly well supported by the available evidence. While such behavior is not exactly lying – inasmuch as the people making these claims don’t necessarily know they’re engaged in such cognitive distortions – it is certainly on the spectrum of dishonesty, as they would (and do) reject such reasoning otherwise. In the academic world, related kinds of statistical manipulations go by a few names, the one I like the most being “researcher degrees of freedom“. The spirit of this idea refers to the problem of researchers selectively interpreting their data in a variety of ways until they find a result they want to publish, and then omit mentioning all the ways that their data did not work out, or might be interpreted. On that note, here’s a scary statistic: 1-in-3 college men would rape a woman if they could get away with it. Fortunately (or unfortunately, depending on your perspective) the statistic is not at all what it seems.

“…But the researchers failed to adequately report their methods! Spooky!”

The paper in question (Edwards et al, 2014) seeks to try and understand the apparent mystery behind the following finding: when asked if they ever raped anyone, most men will say “no”; when asked instead whether they ever held someone down to coerce them into having sex, a greater percentage of men will indicate that they have. Women’s perceptions about the matter seem to follow suit. As I wrote when discussing the figure that 25% of college women will be raped:

The difference was so stark that roughly 75% of the participants that Koss had labeled as having experiencing rape did not, themselves, consider the experience to be rape.

What strikes me as curious about these findings is not the discrepancy in responses; that much can likely be explained by positing that these questions are perceived by the participants to be asking about categorically different behaviors. After all, if they were actually perceived to be asking about the same thing, you would see a greater agreement between the responses of both men and women between questions, which we do not. Instead, the curious part is that authors – like Edwards et al (2014) – continue to insist that all those participants must be wrong, writing, “…some men who rape do not seem to classify their behavior as such” (Jesse Singal at expresses a similar view, writing: “At the end of the day, after all, the two groups are saying the exact same thing“). Rather than conclude there is something wrong with the questions being asked (such as, say, they are capturing a portion of the population who would have rough, but consensual sex), they instead conclude there is something wrong with everyone else (both men and women) answering them. This latter explanation strikes me as unlikely. 

There’s already something of a bait-and-switch taking place, then, but this is far from the only methodological issue involved in deriving that scary-sounding 1-in-3 figure. Specifically, Edwards et al (2014) asked their 86 male participants to fill out part of the “attraction to sexual aggression” scale (Malamuth, 1989). On this scale, participants are asked to indicate, from 1 to 5, how likely they would be to engage in a variety of behaviors, with a “1″ corresponding to “not likely at all”, while “5″ corresponds to “very likely”. Included on this scale are two questions, one concerning whether the respondent would “rape” a woman, and another asking about whether he would “force her to do something she did not want to do” in a sexual setting. The participants in question were asked about their likelihood of engaging in such behaviors “if nobody would ever know and there wouldn’t be any consequences”. Edwards et al (2014) report that, if such criteria were met, 31% of the men would force a woman to do something sexually, whereas only 13% would rape a woman.

If you’re perceptive, you might have noticed something strange already: that 1-in-3 figure cannot be straightforwardly derived from the sexual aggression scale, as the scale is a 5-point measure, whereas the 1-in-3 statistic is clearly dichotomous. This raises the question of how one translates the scale into a yes/no response format. Edwards et al (2014) do not explicitly mention how they managed such a feat, but I think the answer is clear from the labeling in one of their tables: “Any intention to rape a woman” (emphasis, mine). What the researchers did, then, was code any response other than a “1″ as an affirmative; the statistical equivalent of saying that 2 is closer to 5 than it is to 1. In other words, the question was, “Would you rape a woman if you could get away with it”, and the answers were, effectively, “No, Yes, Yes, Yes, or Yes”. Making the matter even worse is that all that participants were answering both questions. This means they saw a question asking about “rape” and another question about “forcing a woman to do something she didn’t want to”. As participants likely figured that there was no reason the researchers would be asking the same question twice, they would have very good reason for thinking that these questions refer to categorically different things. For the authors to then conflate the two questions after the fact as being identical is stunningly disingenuous.

“The problem isn’t me; it’s everyone else”

To put these figures in better context, we could consider the results reported by Malamuth (1989). In response to the “Would you rape if you wouldn’t get caught” question, 74% of men indicated “1″ and 14% indicated a “2″, meaning a full 88% of them fell below the midpoint of the scale; by contrast, only 7% fell above the midpoint, with about 5% indicating a “4″ and 2% indicating a “5″. Of course, reporting that “1-in-3 men would rape” if they could get away with it is much different than saying “less than 1-in-10 probably would”. The authors appear interested in deriving the most-damning interpretation of their data possible, however, as evidenced by their unreported and, in my mind, unjustifiable grouping of the responses. That fact alone should raise alarm bells as to whether the statistics they provide you would do a good job of predicting reality.

But let’s go ahead and take these responses at face value anyway, even if we shouldn’t: somewhere between 10-30% of men would rape a woman if there were no consequences for doing so. How alarming should that figure be? On the first front, the hypothetical world of “no consequence” doesn’t exist. Some proportion of men who would be interested in doing such things are indeed restrained from doing so by the probability of being punished. Even within that hypothetical world of freedom from consequences, however, there are likely other problems to worry about, in that you will always find some percentage of the population willing to engage in anti-social behavior that harms others when there are no costs for doing so (in fact, the truly strange part is that lots of people indicate they would avoid such behaviors).

Starting off small, for instance, about 70% of men and women indicate that they would cheat on their committed partner if they wouldn’t get caught (and slightly over 50% have cheated in spite of those possible consequences). What about other acts, like stealing, or murder. How many people might kill someone else if there would be no consequences for it? One informal poll I found placed that number around 40%; another puts it a little above 50% and, when broken up by sex, 32% of women would and a full 68% of men would. Just let those numbers sink in for a moment: comparing the two numbers for rape and murder, the men in Edwards et al (2014) were in between 2-to-7 times less likely to say they would rape a woman than kill someone if they could, depending on how one interprets their answers. That’s a tremendous difference; one that might even suggest that rape is viewed as a less desirable activity than murder. Now that likely has quite a bit to do with some portion of that murder being viewed as defensive in nature, rather than exploitative, but it’s still some food for thought.

 There are proportionately fewer defensive rapes than defensive stabbings…

This returns us nicely to the politics of fear. The last post addressed people purposefully downplaying the risks posed by terrorist attacks; in this case, we see people purposefully inflating the reported propensities to rape. The 1-in-3 statistic is clearly crafted in the hopes of making an issue seem particularly threatening and large, as larger issues tend to have more altruism directed towards them in the hopes of a solution. As there are social stakes in trying to make one’s problems seem especially threatening, however, this should immediately make people skeptical when dealing with such statistics for the same reasons you shouldn’t let me tell you about how smart or nice I am. There is a very real risk of artificially trying to puff one’s statistics up, as people might come to eventually start not trusting you about things as the default, even for different topics entirely; this should hold true especially if they belong to a group targeted by such misleading results. The undesirable outcomes of such a process being, rather than increases in altruism and sympathy devoted to a real problem, apathy and hostility. Lessons learned from fables like The Boy Who Cried Wolf are timely as ever, it would seem.

References: Edwards, S., Bradshaw, K., & Hinsz, V. (2014). Denying rape but endorsing forceful intercourse: Exploring differences among responders. Violence & Gender, 1, 188-193.

Malamuth, N. (1989). The attraction to sexual aggression scale: Part 1. The Journal of Sex Research, 26, 26-49.

The Politics Of Fear

There’s an apparent order of operations frequently observed in human reasoning: politics first, facts second. People appear perfectly willing to accept flawed arguments or incorrect statistics they would otherwise immediately reject, just so long as they support the reasoner’s point of view; Greg Cochran documented a few such cases (in his simple and eloquent style) a few days ago on his blog. Such a bias in our reasoning ability is not only useful – inasmuch as persuading people to join your side of a dispute tends to carry benefits, regardless of whether you’re right or wrong – but it’s also common: we can see evidence of it in every group of people, from the uneducated to those with PhDs and decades of experience in their field. In my case, the most typical contexts in which I encounter examples of this facet of our psychology – like many of you, I would suspect – is through posts shared or liked by others on social media. Recently, these links have been cropping up concerning the topic of fear. More precisely, there are a number of writers who think that people (or at least those who disagree with them) are behaving irrationally regarding their fears of Islamic terrorism and the threat it poses to their life. My goal here is not to say that people are being rational or irrational about such things – I happen to have a hard time finding substance in such terms – but rather to provide a different perspective than the ones offered by the authors; one that is likely in the minority among my professional and social peers.

You can’t make an omelette without alienating important social relations 

The first article on the chopping block was published on the New York Times website in June of last year. The article is entitled, “Homegrown extremists tied to deadlier toll than Jihadists in U.S. since 9/11,” and it attempts to persuade the reader that we, as a nation, are all too worried about the threat Islamic terrorism poses. In other words, American fears of terrorism are wildly out of proportion to the actual threat it presents. This article attempted to highlight the fact that, in terms of the number of bodies, right-wing, anti-government violence was twice as dangerous as Jihadist attacks in the US since 9/11 (48 deaths from non-Muslims; 26 by Jihadists). Since we seem to dedicate more psychological worry to Islam, something was wrong there There are three important parts of that claim to be considered: first, a very important word in that last sentence is “was,” as the body count evened out by early December in that year (currently at 48 to 45). This updated statistic yields some interesting questions: were those people who feared both types of attacks equally (if they existed) being rational or not on December 1st? Were those who feared right-wing attacks more than Muslim ones suddenly being irrational on the 2nd? The idea these questions are targeting is whether or not fears can only be viewed as proportionate (or rational) with the aid of hindsight. If that’s the case, rather than saying that some fears are overblown or irrational, a more accurate statement would be that such fears “have not yet been founded.” Unless those fears have a specific cut-off date (e.g., the fear of being killed in a terrorist attack during a given time period), making claims about their validity is something that one cannot do particularly well. 

The  second important point of the article to consider is that the count begins one day after a Muslim attack that killed over 3,000 people (immediately; that doesn’t count those who were injured or later died as a consequence of the events). Accordingly, if that count is set back just slightly, the fear of being killed by a Muslim terrorist attack would be much more statistically founded, at least in a very general sense. This naturally raises the question of why the count starts when it does. The first explanation that comes to mind is that the people doing the counting (and reporting about the counting) are interested in presenting a rather selective and limited view of the facts that support their case. They want to denigrate the viewpoints of their political rivals first, and so they select the information that helps them do that while subtly brushing aside the information that does not. That seems like a fairly straightforward case of motivated reasoning, but I’m open to someone presenting a viable alternative point of view as to why the count needs to start when it does (such as, “their primary interest is actually in ignoring outliers across the board”).    

Saving the largest for last, the final important point of the article to consider is that it appears to neglect the matter of base rates entirely. The attacks labeled as “right-wing” left a greater absolute number of bodies (at least at the time it was written), but that does not mean we learned right-wing attacks (or individuals) are more dangerous. To see why, we need to consider another question: how many bodies should we have expected? The answer to that question is by no means simple, but we can do a (very) rough calculation. In the US, approximately 42% of the population self-identifies as Republican (our right-wing population), while about 1% identifies as Muslim. If both groups were equally likely to kill others, then we should expect that the right-wing terrorist groups leave 42 bodies for every 1 that the Muslim group do. That ratio would reflect a genuine parity in threat. A count suggesting that this ratio was 2-to-1 at the time it written, and was 1-to-1 later that same year, we might reasonably conclude that the Muslim population, per individual member, is actually quite a bit more prone to killing others in terrorist attacks; if we factor in the 9/11 number, that ratio becomes something closer to 0.01-to-1, which is a far cry from demographic expectations.

Thankfully, you don’t have to report inconvenient numbers

Another example comes from The New Yorker, published just the other day (perhaps is it something about New York that makes people publish these pieces), entitled, “Thinking rationally about terror.” The insinuation, as before, is that people’s fears about these issues do not correspond well to the reality. In order to make the case that people’s fears are wrongheaded, Lawrence Krauss leans on few examples. One of these concerns the recent shootings in Paris. According to Lawrence, these attacks represented an effective doubling of the overall murder rate in Paris from the previous year (2.6 murders per 100,000 residents), but that’s really not too big of a deal because that just makes Paris as dangerous as New York City, and people aren’t that worried about being killed in NYC (or are they? No data on that point is mentioned). In fact, Lawrence goes on to say, the average Paris resident is about as likely to have been killed in a car accident during any given year than to have been killed during the mass shooting. This point is raised, presumably, to highlight an irrationality: people aren’t concerned about being killed by cars for the most part, so they should be just as unconcerned about being killed by a terrorist if they want to be rational.

This point about cars is yet another fine example of an author failing to account for base rates. Looking at the raw body count is not enough, as people in Paris likely interact with hundreds (or perhaps even thousands; I don’t have any real sense for that number) of cars every day for extended periods of time. By contrast, I would imagine Paris residents interact markedly less frequently with Muslim extremists. Per unit of time spent around cars, they would pose what is likely a much, much lower threat of death than Muslim extremists. Further, people do fear the harm caused by cars (we look both ways before crossing a street, we restrict licenses to individuals who demonstrate their competence to handle the equipment, have speed limits, and so on), and it is likely that the harm they inflict would be much greater if such fears were not present. In much the same way, it is also possible that the harms caused by terrorist groups would be much higher if people decided that such things were not worth getting worked up about and took no steps to assure their safety early on. Do considerations of these base rates and future risks fall under the umbrella of “rational” thinking? I would like to think so, and yet they seemed so easily overlooked by someone chiding others for being irrational: Lawrence at least acknowledges that future terror risks might increase for places like Paris, but notes that that kind of life is pretty much normal for Israel; the base-rate problems is not even mentioned.

While there’s more I could say on these topics, the major point I hope to get across is this: if you want to know why people experience fear about certain topics, it’s probably best to not start your analysis with the assumption that these people are wrong to feel the way they do. Letting one’s politics do the thinking is not a reliable way to get at a solid understanding of anything, even if it might help further your social goals. If we were interested in understanding the “why” behind such fears, we might begin, for instance, with the prospect that many people likely fear historically-relevant, proximate cues of danger, including groups of young, violent males making threats to your life based on your group membership, and cases where those threats are followed through and made credible. Even if such individuals currently reside many miles away, and even if only a few such threats have been acted upon, and even if the dangerous ones represent a small minority of the population, fearing them for one’s own safety does not – by default – seem to be an unreasonable thing to do; neither does fearing them for the safety of one’s relatives, social relations, or wider group members.

“My odds of getting hurt were low, so this isn’t worth getting worked up over”

Now, as I mentioned, all of this is not to say that people ought to fear some particular group or not; my current interests do not reside in directing your fears or their scope. I have no desire to tell you that your fears are well founded or completely off base (in no small part because I earnestly don’t know if they are). My interests are much more general than that, as this kind of thinking is present in all kinds of different contexts. There’s a real problem in beginning with the truth of your perspective and beginning your search for evidence only after the fact. The problem can run so deep that I actually find myself surprised to see someone take up the position that they were wrong after an earnest dig through the available evidence. Such an occurrence should be commonplace if rationality or truth were the goal in these debates, as people get things wrong (at least to some extent) all the time, especially when such opinions are formed in advance of such knowledge. Admissions of incorrect thinking does require, however, that one is willing to, at least occasionally, sacrifice a belief that used to be held quite dear; it requires looking like a fool publicly now and again; it even requires working against your own interests sometimes. These are things you will have to do; not just things that the opposition will. As such, I suspect these kinds of inadequate lines of reasoning will continue to pervade such discussions, which is a bit of a problem when the lives of others literally hang in the balance of the outcome.