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What Does Revenge Want?

hellocopyIn The Princess Bride, the Spanish swashbuckler Inigo Montoya (played memorably by Mandy Patinkin), is the poster child for the seductive power of revenge. Montoya is a man whose entire adult life has been directed and shaped by his desire to avenge the death of his father. (The scene in which he ultimately fulfills this central goal of his life can be seen here in this YouTube clip. Only a few weeks ago did I realize that the other actor in this scene is the great Christopher Guest).

History provides us with other fascinating examples of the compelling power of the desire for revenge: Geronimo, the famous Apache warrior, describes his satisfaction after the slaughter of the Mexican forces that had massacred his mother, wife, and children only a year before: “Still covered in the blood of my enemies, still holding my conquering weapon, still hot with the joy of battle, victory, and vengeance, I was surrounded by the Apache braves and made war chief of all the Apaches. Then I gave orders for scalping the slain. I could not call back my loved ones, I could not bring back the dead Apaches, but I could rejoice in this revenge.[1] In Blood Revenge, the anthropologist Chris Boehm recounts how one of his informants described how a tribal Montenegrin typically feels after taking revenge against an enemy: “[H]e is happy; then it seems to him that he has been born again, and as a mother’s son he takes pride as though he had won a hundred duels.”[2]

Inigo Montoya, Geronimo, and tribal Montenegrins notwithstanding, the notion that revenge brings satisfaction does not sit easily with all psychologists. Kevin Carlsmith, Tim Wilson, and Dan Gilbert published a paper in 2008, for instance, that seemed to suggest that people only believed that revenge would bring satisfaction.[3] The notion that revenge was satisfying was, the authors suspected, another example of affective forecasting (an idea that I generally like, by the way): people only think that revenge is satisfying. They found that people did indeed expect to feel better after seeking revenge, but when given an actual opportunity to punish a bad guy after mistreatment in the lab, Carlsmith and colleagues found that avengers actually felt less satisfied than did victims who stayed their hands.

The Carlsmith et al. finding—people only think revenge will make them feel better, when it in fact makes them feel worse—has become a kind of psychological truism about revenge. Just yesterday, for example, this bit of common knowledge got repeated in an otherwise excellent article on revenge that appeared in the New York Times. In the article, Kate Murphy writes, “But the thing is, when people take it upon themselves to exact revenge, not only does it fail to prevent future harm but it also ultimately doesn’t make the avenger feel any better. While they may experience an initial intoxicating rush, research indicates that upon reflection, people feel far less satisfied after they take revenge than they imagined.”

But Murphy’s claim ignores a lot of data that indicates otherwise.[4] A series of experiments from Mario Gollwitzer and his colleagues have shown that people are in fact capable of experiencing just as much satisfaction from revenge as they were hoping for, especially when they become aware that the transgressor has learned a lesson from the punishment and has decided to mend his or her ways as a result of it. What revenge wants, it appears, is not simply to lob a grenade over a wall at a bad guy, or to blow off a little steam. Instead, what revenge wants is a reformed scoundrel—an offender who both realizes that what he or she has done to a victim was morally wrong and who acknowledges his or her intent to avoid harming the avenger again in the future. When revenge accomplishes these goals, it seems, it really does satisfy. The bad guy has been deterred from repeating his or her harmful actions. The goal has been accomplished. The itch has been scratched.

Let me be clear: Revenge is bad. It’s bad for relationships (generally), it’s bad for business, it’s bad for societies, and it’s bad for world peace. It’s probably even bad for your health. I’ve never met anybody who wanted more revenge in the world (except, of course, they were the wronged party). But no one has ever gotten rid of any bad thing in the world by understanding it less clearly. Ugly or not, revenge that finds its target can be as exhilarating as winning the Super Bowl. Once we really understand that revenge wants deterrence, we’ll be in a better position to create institutions that can provide alternative means of scratching the itch.

Boehm, C. (1987). Blood revenge: The enactment and management of conflict in Montenegro and other tribal societies (2nd ed.). Philadelphia: University of Pennsylvania Press.

Carlsmith, K. M., Wilson, T. D., & Gilbert, D. T. (2008). The paradoxical consequences of revenge. Journal of Personality and Social Psychology, 95, 1316-1324. doi: 10.1037/a0012165

Funk, F., McGeer, V., & Gollwitzer, M. (2014). Get the message: Punishment is satisfying if the transgressor responds to its communicative intent. Personality and Social Psychology Bulletin, 0146167214533130. doi: 10.1177/0146167214533130

Geronimo. (1983). Geronimo’s story of his life. New York: Irvington.

Gollwitzer, M., & Denzler, M. (2009). What makes revenge sweet: Seeing the offender suffer or delivering a message? Journal of Experimental Social Psychology, 45, 840-844. doi: 10.1016/j.jesp.2009.03.001

Gollwitzer, M., Meder, M., & Schmitt, M. (2011). What gives victims satisfaction when they seek revenge? European Journal of Social Psychology, 41, 364-374. doi: 10.1002/ejsp.782

[1] Geronimo (1983).

[2] Boehm (Boehm, 1987).

[3] Carlsmith, Wilson, and Gilbert (2008).

[4] Funk, McGeer, and Gollwitzer (2014); Gollwitzer and Denzler (2009); Gollwitzer, Meder, and Schmitt (2011).

A P-Curve Exercise That Might Restore Some of Your Faith in Psychology

I teach my university’s Graduate Social Psychology course, and I start off the semester (as I assume many other professors who teach this course do) by talking about research methods in social psychology. Over the past several years, as the problems with reproducibility in science have become more and more central to the discussions going on in the field, my introductory lectures have gradually become more dismal. I’ve come to think that it’s important to teach students that most research findings are likely false, that there is very likely a high degree of publication bias in many areas of research, and that some of our most cherished ideas about how the mind works might be completely wrong.

In general, I think it’s hard to teach students what we have learned about the low reproducibility of many of the findings in social science without leaving them with a feeling of anomie, so this year, I decided to teach them how to do p-curve analyses so that they would at least have a tool that would help them to make up their own minds about particular areas of research. But I didn’t just teach them from the podium: I sent them away to form small groups of two to four students who would work together to conceptualize and conduct p-curve analysis projects of their own.

I had them follow the simple rules that are specified in the p-curve user’s guide, which can be obtained here, and I provided a few additional ideas that I thought would be helpful in a one-page rubric. I encouraged them to make sure they were sampling from the available population of studies in a representative way. Many of the groups cut down their workload by consulting recent meta-analyses to select the studies to include. Others used Google Scholar or Medline. They were all instructed to follow the p-curve manual chapter-and-verse, and to write a little paper in which they summarized their findings. The students told me that they were able to produce their p-curve analyses (and the short papers that I asked them to write up) in 15-20 person-hours or less. I cannot recommend this exercise highly enough. The students seemed to find it very empowering.

This past week, all ten groups of students presented the results of their analyses, and their findings were surprisingly (actually, puzzlingly) rosy: All ten of the analyses revealed that the literatures under consideration possessed evidentiary value. Ten out of ten. None of them showed evidence for intense p-hacking. On the basis of their conclusions (coupled with the conclusions that previous meta-analysts had made about the size of the effects in question), it does seem to me that there really is license to believe a few things about human behavior:

(1) Time-outs really do reduce undesirable behavior in children (parents with young kids take notice);

(2) Expressed Emotion (EE) during interactions between people with schizophrenia and their family members really does predict whether the patient will relapse in in the successive 9-12 months (based on a p-curve analysis of a sample of the papers reviewed here);

(3) The amount of psychological distress that people with cancer experience is correlated with the amounts of psychological distress that their caregivers manifest (based on a p-curve analysis of a sample of the papers reviewed here);


(4) Men really do report more distress when they imagine their partners’ committing sexual infidelity than women do (based on a p-curve analysis of a sample of the papers reviewed here; caveats remain about what this finding actually means, of course…)

I have to say that this was a very cheering exercise for my students as well as for me. But frankly, I wasn’t expecting all ten of the p-curve analyses to provide such rosy results, and I’m quite sure the students weren’t either. Ten non-p-hacked literatures out of ten? What are we supposed to make of that? Here are some ideas that my students and I came up with:

(1) Some of the literatures my students reviewed involved correlations between measured variables (for example, emotional states or personality traits) rather than experiments in which an independent variable was manipulated. They were, in a word, personality studies rather than “social psychology experiments.” The major personality journals (Journal of Personality, Journal of Research in Personality, and the “personality” section of JPSP) tend to publish studies with conspicuously higher statistical power than do the major journals that publish social psychology-type experiments (e.g., Psychological Science, JESP and the two “experimental” sections of JPSP), and one implication of this fact, as Chris Fraley and Simine Vazire just pointed out is that the former set of experiment-friendly journals are more likely, ceteris paribus, to have higher false positive rates than is the latter set of personality-type journals.

(2) Some of the literatures my students reviewed were not particularly “sexy” or “faddish”–at least not to my eye (Biologists refer to the large animals that get the general public excited about conservation and ecology as the “charismatic megafauna.” Perhaps we could begin talking about “charismatic” research topics rather than “sexy” or “faddish” ones? It might be perceived as slightly less derogatory…). Perhaps studies on less charismatic topics generate less temptation among researchers to capitalize on undisclosed researcher degrees of freedom? Just idle speculation…

(3) The students went into the exercise without any a priori prejudice against the research areas they chose. They wanted to know whether the literatures the focused on were p-hacked because they cared about the research topics and wanted to base their own research upon what had come before–not because they had read something seemingly fishy on a given topic that gave them impetus to do a full p-curve analysis. I wonder if this subjective component to the exercise of conducting a p-curve analysis is going to end up being really significant as this technique becomes more popular.

If you teach a graduate course in psychology and you’re into research methods, I cannot recommend this exercise highly enough. My students loved it, they found it extremely empowering, and it was the perfect positive ending to the course. If you have used a similar exercise in any of your courses, I’d love to hear about what your students found.

By the way, Sunday will be the 1-year anniversary of the Social Science Evolving Blog. I have appreciated your interest.  And if I don’t get anything up here before the end of 2014, happy holidays.

Do Humans Have Innate Concepts for Thinking About Other People?

Gossip is one of life’s greatest consolations and one of our most reliable conversational fall-backs. In a world without gossip, many of us could realize Tim Ferriss’s ideal of a Four-Hour Work Week without even putting any of his advice into practice. Gossip is also, according to the anthropologist Donald Brown (1991), a human universal—one of those pan-human traits that people within every world society can be expected to evince.

Our ability to gossip, as is the case with all ostensive communication, is premised on the idea that our listeners are in possession of concepts that enable them to convert the sounds coming out of our mouths into ideas that resemble those we are trying to convey. Which got me to thinking about the psychology that makes gossip possible: Are there universal “person concepts”—species-typical cognitive representations of particular human traits or attributes—that every human reliably acquires during normal development? If you flew back from your vacation in Tanzania with a Hadza man or woman whom you planned to entertain in your home for a couple of weeks, would the two of you be able to settle into your living room and enjoy a little TMZ* (assuming you spoke Hadza and could translate)? The Hadza are arguably the last full-time hunter-gatherer society on the planet; it’s difficult to imagine a society more different from our own. Could you trust that your Hadza friend had acquired all of the person concepts that would enable him or her to follow the action? Are there any universal and native social concepts upon which all humans rely in order to make social life work?

I’ll get to that in a moment, but first a slightly bigger question: Does the mind contain any native concepts at all? Here in 21st century, many scholars in the social sciences would answer this question affirmatively, having turned their backs on the most hardcore versions of the Blank Slate theory that Steven Pinker describes in his aptly titled (2002) book, The Blank Slate. (The Major Blank-Slater of Western thought, John Locke, famously wrote “If we will attentively consider new-born children, we shall have little reason to think that they bring many ideas into the world with them.”). Even so, there is still much to be debated and discovered about innate ideas.

For starters, how many innate ideas are there? Conceding that there are more than zero of them is not a particularly bold claim. Are there handfuls? Dozens? Scores? Many evolutionary psychologists and cognitive scientists prefer large numbers here, and not without good reason: It’s difficult to imagine how even the basic behavioral tasks that humans must accomplish to stay alive—finding food, water, and warmth, for starters—could be accomplished unless the mind contained some built-in conceptual content.

To Find Food, a Newborn Baby Needs FOOD

Since Locke brought up the case of “new-born children,” let’s think about babies for a moment. A newborn infant comes into the world with a pressing problem: She must find something to eat. Locke thought the infant came into the world with the ability to experience hunger, but he did not think the infant came into the world with a concept of FOOD. The so-called Frame Problem, which Daniel Dennett (2006) so vividly described, makes it unlikely that a newborn infant could solve this problem (“Find food”) before it starved unless it had some built-in representation of what FOOD is. The selection pressure for the evolution of a conceptual short-cut here is enormous: Successful food-finding in the first hour after birth is a predictor of infant survival, so that first hour matters. The clock is ticking. Therefore, a cognitive design that requires infants to find food on a blind trial-and-error basis is likely to be a losing design in comparison to a design that comes with a built-in concept for FOOD from the outset.

For human infants, the FOOD concept involves the activity of neurons that respond to the olfactory properties of specific volatile chemicals that human mothers emit via the breast, possibly along with visual and tactile features of the human breast as well (Schaal et al., 2009). Through a matching-to-template process, human infants can quickly locate breast-like objects in their environments, which of course are the only objects in the universe that are specially designed to provide human neonates with nutrition and hydration.

What about More “Complex” Concepts?

Convincing you that human neonates possess an innate concept for FOOD is perhaps an easy sell, but in a recent paper in Current Directions in Psychological Science, Andy Delton and Aaron Sell (2014) argued that humans come to possess a variety of universal and reliably developing social concepts as well, which enable them to regulate the universal components of human social life. For Delton and Sell, there can be “no motivation without representation,” so if there are certain adaptive challenges that humans have evolved behavioral programs to surmount, there should also be concepts within the human mind that enable them to parse their worlds into adaptively meaningful units so that the stimuli that are relevant to achieving those adaptive goals can be easily identified.

Delton and Sell’s list of candidates for intuitive concepts (which they in no way claim to be exhaustive) includes COOPERATOR, FREE RIDER, NEWCOMER, KINSHIP, ROMANTIC PARTNER, ROMANTIC RIVAL, ENTITLEMENT, DISRESPECT, INGROUP, and OUTGROUP, among others (see the Table below). The claim here, again, is that if humans are going to have evolved goals that involve “establishing cooperative relationships,” “deterring free riders,” or “evaluating whether to engage in trade with someone from an outgroup,” they will need concepts to represent what COOPERATORS, FREE RIDERS, and OUTGROUPS actually are. There can be no motivation without representation.

(By the way, to claim that such concepts are “innate” or “native” is not to claim that they are present in the mind from birth, but rather, that the human genome possesses the programs for assembling these representations within the mind at developmentally appropriate points in the human life cycle, and with appropriate kinds of environmental inputs. Concepts come and concepts go as we develop. Think of how the concept of FOOD gets overwritten once infants turn away from breast milk and toward other foods during the first three to four years of life. The FOOD concept within the mind/brain changes over ontogeny, but the genes that give rise to that initial FOOD concept—which the infants match against environmental inputs on the basis of the olfactory, visual, and tactile information—remain in the genome and are passed onto one’s genetic heirs so the concept can be re-constructed during ontogeny.)

Delton-Sell-Figure1From Delton and Sell, 2014

Looking for Universal Concepts in the Dictionary

Another paper was recently published that provides some confirmatory evidence, of a sort, for Delton and Sell’s position. The personality psychologist Gerard Saucier and his colleagues (2014) read through the English dictionaries representing the languages of 12 geographically and linguistically distinct cultural groups from all over the world (see Table below) in hopes of finding the universal concepts that humans use to parse up the actions and dispositions of other humans.

Saucier_Figure1From Saucier et al., 2014

The logic behind Saucier et al.’s effort was straightforward: All human societies should end up making words to represent the attributes that humans universally use to parse their social lives—presuming, I suppose, that those concepts are worth talking about. (Universal social concepts for which humans universally make words might be only a subset of all universal social concepts: Some universal social concepts might not be worth talking about, though I can’t think off-hand of what such concepts might be. Can you?)

By scouring these dictionaries, Saucier and colleagues ultimately located nearly 17,000 words across the 12 languages that could be used to refer to human attributes. Through a reduction process that enabled them to thrown out synonyms and variations on common roots (fool, foolish, foolishly, “to fool,” and “to be fooled” can all be reduced to a single attribute concept, as can all of the other words that gloss in English as “to be foolish”), they were able to greatly simplify the number of attribute concepts within each language to more manageable numbers.

Having reduced each language’s human attribute lexicon down in this fashion, they then looked for attribute terms that cropped up in either (a) all 12 of the languages they studied; or (b) 11 of the 12 languages they studied. With their “11 out of 12” rule, they were taking a cue from the anthropologist Donald Brown, who argued that “Human Universals” should be manifest in the ethnographic materials for 95% of the world’s societies. Placing the empirical estimate at 100% would be too strict because it doesn’t allow for ethnographers’ oversights. With only 12 dictionaries to work with, 11 out of 12 is as close as you can come to 95%.

What Saucier and colleagues discovered was fascinating. All twelve languages had human attribute concepts corresponding to BAD, GOOD, USELESS, BEAUTIFUL, DISOBEDIENT, STUPID, ALIVE, BLIND, SICK, STRONG, TIRED, WEAK, WELL, AFRAID, ANGRY, ASHAMED, JEALOUS, SURPRISED, BIG, LARGE, SMALL, HEAVY, OLD, and YOUNG. If you use the slightly more lenient “11 out of 12” criterion for judgments of universality, you get to add EVIL, HANDSOME, GOSSIP, HUMBLE, LOVE, CLUMSY, DRUNK, FOOLISH, QUICK, SLOW, UNABLE, WISE, DEAD, SLEEPY, HUNGRY, PAIN, PLEASURE, THIRSTY, HAPPY, SATISFIED, TROUBLED, FAT, LITTLE, SHORT, TALL, MARRIED, POOR, RICH, and STRANGER.

To me, this is a fascinating list. Some of the traits on the list involve moral evaluation (e.g., BAD, GOOD, EVIL, HUMBLE). Others clearly have to do with physical health, condition, or capacity for work (e.g., ALIVE, BLIND, SICK, WELL, QUICK, SLOW, UNABLE, STRONG, WEAK). Others relate to reproductive value (e.g., BEAUTIFUL, HANDSOME, MARRIED), and age (YOUNG, OLD). Many of the universals relate to more temporary motivations, emotions, and behavioral dispositions (e.g., TIRED, AFRAID, ANGRY, ASHAMED, JEALOUS, SURPRISED, PLEASURE, THIRSTY, HUNGRY, PAIN, COLD, HOT). And still others are associated with reliability and judgment (e.g., CLUMSY, WISE, RIGHT, USELESS). I think Delton and Sell would be especially pleased to see that STRANGER even makes it to the list—consistent with their speculation that humans possess innate “NEWCOMER TO A COALITION” and “OUTGROUP” concepts.

I wouldn’t want to overstate the significance of Saucier and colleagues’ findings (although I think the findings are extremely important): As I mentioned above, just because we lack a word for something doesn’t mean we don’t have an innate concept for it (remember that infants can find food because they come into the world with a well-developed FOOD concept, even though they can’t converse with you about food). Saucier’s list of universal person words almost surely does not exhaust the list of evolved person concepts that humans reliably acquire through ontogeny, but it might be a decent rough draft of the set of person concepts that all adults eventually find regular occasions to gossip about. And of course, if you can count on the fact that your Hadza houseguest has concepts for Bad, Good, Beautiful/Handsome, Love, Drunk, Sick, Ashamed, Jealous, Fat, Short, Old, Young, Rich, and Poor, then translating an episode of TMZ for him or her should be no trouble whatsoever.

Postscript: After reading this post, Paul Bloom wrote me to ask why I “didn’t mention the enormous  developmental psych literature that looks at exactly this question—work that studies babies with an eye toward exploring exactly which concepts are innate and which are learned, e.g., Carey, Baillergeon, Wynn, Spelke, Gergely, Leslie, and so on.” (Paul was too modest, I think, to put himself to this list, but he should have.) Hat in hand, I couldn’t agree more. If you don’t know the work of the scientists that Paul mentioned above, you can look to it for further evidence that humans come into the world with complex social concepts. ~MEM


Brown, D. E. (1991). Human universals. Boston, MA: McGraw-Hill.

Delton, A. W., & Sell, A. (2014). The co-evolution of concepts and motivation. Current Directions in Psychological Science, 23(2), 115-120.

Dennett, D. C. (2006). Cognitive wheels: The Frame Problem of AI. New York: Routledge.

Pinker, S. (2002). The blank slate: The modern denial of human nature. New York: Viking.

Saucier, G., Thalmayer, A. G., & Bel-Bahar, T. S. (2014). Human attribute concepts: Relative ubiquity across twelve mutually isolated languages. Journal of Personality and Social Psychology, 107(1), 199-216.

Schaal, B., Coureaud, G., Doucet, S., Delaunay-El Allam, M., Moncomble, A.-S., Montigny, D., . . . Holley, A. (2009). Mammary olfactory signalisation in females and odor processing in neonates: Ways evolved by rabbits and humans. Behav Brain Res, 200, 346-358.

*I trust that you were able to infer that by TMZ I meant the celebrity gossip show and not the cancer drug or the Soviet motorcycle manufacturer.

The Myth of Moral Outrage

This year, I am a senior scholar with the Chicago-based Center for Humans and Nature. If you are unfamiliar with this Center (as I was until recently), here’s how they describe their mission:

The Center for Humans and Nature partners with some of the brightest minds to explore humans and nature relationships. We bring together philosophers, biologists, ecologists, lawyers, artists, political scientists, anthropologists, poets and economists, among others, to think creatively about how people can make better decisions — in relationship with each other and the rest of nature.

In the year to come, I will be doing some writing for the Center, starting with a piece I that has just appeared on their web site. In The Myth of Moral Outrage, I attack the winsome idea that humans’ moral progress over the past few centuries has ridden on the back of a natural human inclination to react with a special kind of anger–moral outrage–in response to moral violations against unrelated third parties:

It is commonly believed that moral progress is a surfer that rides on waves of a peculiar emotion: moral outrage. Moral outrage is thought to be a special type of anger, one that ignites when people recognize that a person or institution has violated a moral principle (for example, do not hurt others, do not fail to help people in need, do not lie) and must be prevented from continuing to do so . . . Borrowing anchorman Howard Beale’s tag line from the film Network, you can think of the notion that moral outrage is an engine for moral progress as the “I’m as mad as hell and I’m not going to take this anymore” theory of moral progress.

I think the “Mad as Hell” theory of moral action is probably quite flawed, despite the popularity that it has garnered among may social scientists who believe that humans possess “prosocial preferences” and a built-in (genetically group-selected? culturally group selected?) appetite for punishing norm-violators. I go on to describe the typical experimental result that has given so many people the impression that we humans do indeed possess prosocial preferences that motivate us to spend our own resources for the purpose of punishing norm violators who have harmed people whom we don’t know or otherwise care about. Specialists will recognize that the empirical evidence that I am taking to task comes from that workhorse of experimental economics, the third-party punishment game:

…[R]esearch subjects are given some “experimental dollars” (which have real cash value). Next, they are informed that they are about to observe the results of a “game” to be played by two other strangers—call them Stranger 1 and Stranger 2. For this game, Stranger 1 has also been given some money and has the opportunity to share none, some, or all of it with Stranger 2 (who doesn’t have any money of her own). In advance of learning about the outcome of the game, subjects are given the opportunity to commit some of their experimental dollars toward the punishment of Stranger 1, should she fail to share her windfall with Stranger 2.

Most people who are put in this strange laboratory situation agree in advance to commit some of their experimental dollars to the purpose of punishing Stranger 1’s stingy behavior. And it is on the basis of this finding that many social scientists believe that humans have a capacity for moral outrage: We’re willing to pay good money to “buy” punishment for scoundrels.

In the rest of the piece, I go on to point out the rather serious inferential limitations of the third-party punishment game as it is typically carried out in experimental economists’ labs. I also point to some contradictory (and, in my opinion, better) experimental evidence, both from my lab and from other researchers’ labs, that gainsay the widely accepted belief in the reality of moral outrage. I end the piece with a proposal for explaining what the appearance of moral outrage might be for (in a strategic sense), even if moral outrage is actually not a unique emotion (that is, a “natural kind” of the type that we assume anger, happiness, grief, etc. to be) at all.

I don’t want to steal too much thunder from the Center‘s own coverage of the piece, so I invite you to read the entire piece over on their site. Feel free to post a comment over there, or back over here, and I’ll be responding in both places over the next few days.

As I mentioned above, I’ll be doing some additional writing for the center in the coming six months or so, and I’ll be speaking at a Center event in New York City in a couple of months, which I will announce soon.

Happy International Forgiveness Day!

August is a notoriously slow month for news (and blogging). It’s also somewhat bereft of holidays and official days of observance. According to the web site Holiday Insights, August does host a few official holidays (that is, days of observance that were established by presidential proclamation or acts of Congress). These include U.S. Coast Guard Day, National Lighthouse Day, Aviation Day, Senior Citizen’s Day, and Women’s Equality Day. The unofficial August holidays, I have just learned, also include National Dog Day, Presidential Joke Day (on August 11, 1984, President Reagan joked into a live microphone that the U.S. had officially outlawed “Russia” and would begin bombing five minutes thereafter), and Vesuvius Day (take a guess). But these are the exceptions that prove the rule: August is a month in which we’re not encouraged to be mindful of very much.

Even so, over the past couple of years, I’ve become rather fond of today, the first Sunday in August: This is the day on which a group called the Worldwide Forgiveness Alliance is trying to establish a worldwide observance of International Forgiveness Day. I don’t know anything about this group, other than what is posted on their web site, but their self-described mission is “to evoke the healing spirit of Forgiveness worldwide.” I don’t think they’re taking their cues from scholarly writings or scientific research on forgiveness, reconciliation, and peacemaking. Instead, it appears to be a truly grassroots movement, trying on a very small scale to encourage forgiveness not only as personal tool for overcoming anger and resentment, but also as a way of repairing relationships between individuals, communities and conflict groups.

For the past 18 years, according to their web site, they have hosted an “International Forgiveness Day” event, and today is no exception. So if you’re out in the Bay Area today, and are curious, you might consider getting out to San Rafael to see what they’re up to. Also, their web site indicates that they will be live-streaming the event here, so I suppose you could celebrate remotely from your deck chair or porch swing.

But perhaps even that feels like more effort than the heat will permit you to expend. I sympathize. If that’s the case, consider sparing a thought for forgiveness today. Or raise two cheers for forgiveness. Or why not make a forgiveness day gazpacho? (This is my plan.) I can think of many worse things to celebrate on a slow, muggy Sunday in August.

The Real Roots of Vengeance and Forgiveness

Yesterday, somebody pointed me to this article, which I wrote a few years ago for a magazine called Spirituality and Health. I had not realized until yesterday that the magazine had made the article available on the web. Even though it’s several years old, I still like the way it reads. In fact, it’s as decent a précis of my book Beyond Revenge as you’re going to find anywhere.

I’m not exactly a regular reader of this particular magazine, but their editorial staff have taken an interest in some of my research and writing over the years, including some of our (by which I mean, my and my collaborators’) work on forgiveness and gratitude, for which I have always been appreciative. The founder of the magazine, whom I was fortunate enough to know, was T. George Harris–one of the most colorful figures in the history of 20th-century magazine publishing. Some readers of this blog might know of George’s work in helping to turn Psychology Today into the behemoth it eventually became, but there is much more to George’s personal and professional life that’s worth knowing about.

George died last year at the age of 89. I found two really nice chronicles of his life–this one from the local San Diego paper (George was a La Jolla resident), and this one written by Stephen Kiesling, who not only is the editor-in-chief at Spirituality and Health, but also was one of George’s closest friends and fondest admirers.


The Trouble with Oxytocin, Part III: The Noose Tightens for The Oxytocin–>Trust Hypothesis be time to see about having that Oxytocin tattoo removed…

When I started blogging six months ago, I kicked off Social Science Evolving with a guided tour of the evidence for the hypothesis that oxytocin increases trusting behavior in the trust game (a laboratory workhorse of experimental economics). The first study on this topic, authored by Michael Kosfeld and his colleagues, created a big splash, but most of the studies in its wake failed to replicate the original finding. I summarized all of the replications in a box score format (I know, I know: Crude. So sue me.) like so:

Box Score_Dec2013By my rough-and-ready calculations, at the end of 2013 there were about 1.25 studies’ worth of successful replications of the original Kosfeld results, but about 3.75 studies’ worth of failed replications (see the original post for details). Even six months ago, the empirical support for the hypothesis that oxytocin increases trust in the trust game was not looking so healthy.

I promised that I’d update my box score as I became aware of new data on the topic, and a brand new study has just surfaced. Shuxia Yao and colleagues had 104 healthy young men and women play the trust game with four anonymous trustees. One of those four trustees (the “fair” trustee) returned enough of the subject’s investment to cause the subject and the trustee to end up with equal amounts of money; the other three trustees (designated as the “unfair players”) declined to return any money to the subject at all.

Next, subjects were randomly assigned to receive either the standard dose of intranasal oxytocin, or a placebo. Forty-five minutes later, participants were told that they would receive an instant message from the four players to whom they had entrusted money during the earlier round of the trust game. The “fair” player from the earlier round, and one of the “unfair” players, sent no message at all. The second unfair player sent a cheap-talk sort of apology, and the third unfair player offered to make a compensatory monetary transfer to the subject that would make their payoffs equal.

Finally, study participants took part in a “surprise” round of the trust game with the same four strangers. The researchers’ key question was whether the subjects who had received oxytocin would behave in a more trusting fashion toward the four players from Round 1 than the participants who received a placebo instead.

They didn’t.

In fact, the only hint that oxytocin did anything at all to participants’ trust behaviors was a faint statistical signal that oxytocin caused female participants (but not male participants) to treat the players from Round 1 in a less trusting way. If anything, oxytocin reduced women’s trust. I should note, however, that this females-only effect for oxytocin was obtained using a statistically questionable procedure: The researchers did not find a statistical signal of an interaction between oxytocin and subjects’ sex, and without such a signal, their separation of the men’s and the women’s data for further analyses really wasn’t licensed. But regardless, the Yao data fail to support the idea that oxytocin increases trusting behavior in the trust game.

It’s time to update the box score:


In the wake of the original Kosfeld findings, 1.25 studies worth of results have accumulated to suggest that oxytocin does increase trust in the trust game, but 4.75 studies worth of results have accumulated to suggest that it doesn’t.

It seems to me that the noose is getting tight for the hypothesis that intransasal oxytocin increases trusting behavior in the trust game. But let’s stay open-minded a while longer. As ever, if you know of some data out there that I should be including in my box score, please send me the details. I’ll continue updating from time to time.

Why Do Honor Killings Defy the First Law of Homicide? And Will Smaller Families Lead to Fewer Of Them?

Few categories of human rights violations more deeply scandalize the liberal (with a little-L) moral sensibility than honor killings do. Reliable numbers are hard to come by, but by most credible accounts it seems likely that several thousand Muslim women each year (and more than a few men) are stoned, burned, hanged, strangled, beheaded, stabbed, or shot to death for the sins of getting raped, falling in love, or dressing immodestly. But to anyone who thinks about human behavior from an evolutionary point of view, honor killings are not just morally outrageous: They’re also really puzzling.

As Martin Daly and Margo Wilson documented in their marvelous book Homicide, killers are very rarely the genetic relatives of their victims. Instead, they’re most often strangers, or rivals, or cuckolded lovers (who, of course, are not each others’ kin even if married—at least, not in the sense that matters to natural selection). Indeed, the typically low level of kinship between the victims of homicides and the people who kill them is so predictable that we could get away with calling it “The First Law of Homicide.” When two genetic relatives are involved in a homicide, it’s usually either as co-victims or co-perpetrators, not as victim and perpetrator.

In a sense, a general reluctance to harm or kill one’s genetic relatives is not exactly breaking news. We’ve understood since William Hamilton’s 1963 and 1964 papers that natural selection creates organisms that appear designed to maximize their inclusive fitness (which incorporates the reproductive success of the individual in whom the gene is physically located, as well as the reproductive success of other individuals who are carrying copies of that gene around) rather than their simple direct fitness. Genes “want” to maximize the total number of copies of themselves that are floating around in the world, even if some of those copies are located in other individuals’ gonads. The principle of kin selection virtually guarantees that we’re walking around with instincts that restrain us from harming our relatives, even when they’ve irritated us. To be clear, I’m not saying people never kill their kin (mental illness is a real wild card here), but the fitness disincentives of doing so were so high as our psychology was evolving that the perceived incentives to do so now have to be very high indeed.

Which is what makes honor killings so puzzling. In a recent article, Andrzej Kulczycki and Sarah Windle summarized data on the circumstances behind more than 300 honor killings across Northern Africa and the Middle East. What jumps off the page when you look at their data is how flagrantly honor killings flout the First Law of Homicide: About three-quarters of honor killings are carried out by family members of the victim. To be specific, the victims’ brothers carry out 29% of them, fathers and (to a much lesser extent, mothers), carry out about 25%, and “other male relatives” carry out an additional 19% of them. (Of the remaining 25%, virtually all are carried out by the victims’ husbands/ex-husbands.)

I’m really interested in that 75% that violate the First Law of Homicide. For the perpetrators of honor killings to over-ride their intuitive aversions to killing their own daughters or sisters, the perceived costs of “dishonor” must be very high indeed. We can’t precisely measure the exact fitness value of honor for someone who lives in a so-called culture of honor, of course, but the link between fitness and honor is undeniable. If you live in an honor culture, your honor determines your (and your children’s) job prospects, marriage prospects, ability to recruit help from neighbors, ability to secure a loan, and protection against those who would otherwise do you harm. Honor is an insurance policy, a social security check, and a glowing letter of recommendation rolled into one bundle. The fitness costs of tarnished honor in an honor culture can be steep.

One of the things I came to appreciate about honor while doing research for one of my books is that honor is a sacred commodity. It doesn’t follow the laws we expect actual physical stuff to obey, or the normal laws of economics, or even the normal rules that govern our everyday psychology. It follows the laws of Sacred Things. If you feel sad one day, you can be pretty sure that the feeling won’t last forever. Dishonor doesn’t work like that. Dishonor doesn’t wash off or fade away with time. Dishonor has to be purged or atoned for. More importantly for my argument here, dishonor does not dilute. The dishonor that a “dishonorable” behavior creates for a family is not like a fixed quantity of scarlet paint that can be used to make only a finite number of scarlet letters. When a young woman “dishonors” her family, there’s enough dishonor to thoroughly cover every one of her brothers and sisters, no matter how many brothers and sisters she has.

There’s an interesting prediction waiting in the wings. If I’m right that dishonor does not dilute, then the perceived fitness-associated costs of a single act of dishonor will be larger for a father and mother with many children than for a father and mother with only with only a few children. This has implications for reducing honor killings. Let me illustrate with a thought experiment.

The Costs of Dishonor to a Father Are Higher in Large Families

Say I am a father with nine children and one of my daughters has done something (or, more likely, has had something done to her) that has brought dishonor upon herself and each of her eight siblings. (Believe me, I am more appalled by having to write sentences like these than you are by having to read them, but I can’t come up with a better way to think through these issues than to try to step into the shoes of someone who is actually factoring honor-related concerns into their social decision-making). As the father of these nine children, the dishonored daughter has reduced my fitness by 9d because each of my children will suffer an honor-related fitness cost of d. (It might be better to quantify the hit to my fitness as 9 * .5 = 4.5 because my genetic relatedness to my children with respect to a rare allele that I possess is 0.5 rather than 1.0, but that won’t change anything in what’s to come. Can we please agree to work with 9 so as to make the math prettier?) So, if I am a father of nine children, and I can restore my family’s honor by murdering my dishonored daughter, I can recover 8d units of fitness (by restoring the damaged honor of my other eight children), and it costs me (I know, the thought sickens me as well) the fitness decrement I suffer through murdering one of my offspring.

If, on the other hand, I have only two children, then the perceived fitness cost of my daughter’s dishonor is 2d (a cost of d is imputed to both of my children), and I’d only be able to recover 1d unit of fitness (for my remaining, unmurdered child) by murdering the dishonored daughter. So, for a father with only two children, the calculus is not so clear: Am I better off in the long run to have two children whose honor is tarnished, or only one child whose honor is restored? For any plausible value of d, it’s hard to imagine that the decision-making scales would tilt in favor of killing the dishonored daughter if doing so would leave you with only one child. I’m betting that the father of two will stay his hand under circumstances in which the father of nine might not.

If I’m right about this, then a demographic shift toward smaller families in developing societies could eventually help to solve the problem of honor killings. I couldn’t find any direct evidence to support this prediction, but Manuel Eisner and Lana Ghuneim recently published a study in which they surveyed 856 Jordanian adolescents from 14 different schools to examine the predictors of their attitudes toward honor killings. They found that even when they controlled for the students’ sex (male vs. female), their religion (Muslim vs. non-Muslim), whether their mothers worked outside of the home (a good proxy for modernization), and the parents’ educational levels (also a good proxy for modern thinking), children with four or more siblings had more favorable attitudes toward honor killings than did children with three or fewer siblings. Not an exact test of my prediction, but to the extent that kids adopt their parents’ views, it seems to me that these results are at least tantalizingly consistent.

Do the human rights groups that want to reduce honor killings and other kinds of honor-related violence around the world ever talk about family size as a truly exogenous (and, in principle, modifiable) cause of honor killings? People are pinning their hopes for solving so many other problems around the world on reductions in family size, so perhaps I’m not being too pie-in-the-sky to add “reductions in honor-related violence” to that list of “Ways In Which We’d Be Better Off If People Had Fewer Kids.” As families shrink, I’m guessing that spared lives become subjectively more valuable than restored family honor.

Why Not Use Cap and Trade to Reduce False Positives In Science? An Elaboration

This post is a longer-form treatment of the Cap and Trade idea for controlling false positives in science that Dave Kelly and I outlined in our brief letter, which appeared in this week’s issue of Nature. It provides more background and additional details that we simply couldn’t cover in a 250-word letter.

First, the background. For the past several years, as many readers are surely aware, a replication crisis has been roiling the sciences. The problem, quite simply, is that some (probably large) proportion of published scientific findings are false. Many remedies have been proposed for addressing the replication crisis, including (1) system-wide changes in how researchers are trained in statistics and research methods; (2) exhortations to greater statistical and methodological virtue among researchers; (3) higher editorial standards for journal editors and reviewers; and (4) journal reforms that would require more transparency from investigators about hypothesis formulation, research methods, data collection, and data analysis as a condition for publication.

Most of these remedies are sensible, but Nature has suggested here and here that NIH officials have been contemplating an even more radical measure: Some sort of audit system in which independent laboratories would be tasked with trying to reproduce recently published scientific results from particular fields. An audit-based system would have its merits, but a cap and trade system might work even better. Our proposal rests on the idea that false positives are a form of pollution: I call it false positive pollution.

False Positives are Pollution

False positives fit the standard economic definition of pollution: They impose opportunity costs on others when they are emitted into the environment. If all published research findings were correct (i.e., if the false discovery rate were zero), then any single conclusion from any single research paper (“Drug X is safe and effective,” say, or “Cap and trade systems reduce false positives in scientific literatures”) could form the basis for confident decision-making. You could read a published paper and then take action on the basis of its conclusions, knowing that those conclusions reflected true states of the world.

However, the more false positive pollution a literature contains, the more costly, on average, it becomes to make decisions on the basis of any published finding. The recent Tamiflu debacle provides a vivid case study: The reason drug companies, governments, and individuals got so excited about Tamiflu as a treatment for flu was that their decision-making was distorted by irreproducible research results. The Tamiflu misadventure features false positive pollution doing what it does best: imposing costs on others, to the tune of $20 billion in wasted public expenditures (not to mention the harm the drugs might have done to their consumers, and the opportunity costs associated with not pursuing possible alternatives).

Likewise, if a published scientific article led you erroneously to believe that a particular laboratory technique was a good way to manipulate some variable in your research, and then you went on to base your PhD work on that technique—only to find that it did not work for you (because it actually doesn’t work for anybody)—then false positive pollution would have caused you to devote time and resources to hocus-pocus rather than the pursuit of something that could have produced actual scientific knowledge. This is one of the costs of false positive pollution that should really bother graduate students, post-docs, and anyone who cares about their career development: Trainees with just as much scientific promise as any other end up wasting their valuable training time on illusions. False positive pollution sets careers back.

A cap and trade system might be useful for reducing false positive pollution in the same way that cap and trade systems have, over the past 45 years, helped to reduce sulphur dioxide, nitrogen oxide, lead additives in gasoline, and even over-fishing. Below, I outline some of the steps we’d need to undertake as a society to implement a cap and trade system to control false positive pollution.

Step 1: Measuring Existing Levels of False Positive Pollution

The first step forward could be to estimate how much false positive pollution is emitted annually, which would require independent replications of random samples of published findings from the prior year. What we would be trying to estimate is the proportion of published experiments, out of the 1.5 million or so that are published each year worldwide, whose results cannot be independently reproduced even when the original protocols are followed exactly. I rather admire the way this was done in the Many Labs Replication Project: Several lab directors agree on the experimental protocol [ideally in collaboration with the investigator(s) who originally published the study] and then go back to their labs and re-run the experiment. The results from all of their independent attempts to replicate are then statistically aggregated to determine whether the original result is a true positive or a false positive.

Expensive, yes, but don’t let the expense distract you for the moment. Good research takes money, and we’re already hemorraging money through the production of false knowledge (keep the image of those warehouses full of Tamiflu vividly in your mind). Why not invest in trying to understand how much money we’re actually wasting and what we might do about it?

Step 2: Determining An Optimal Level of False Positive Pollution

Once we had an estimate of much false positive pollution is emitted annually, we’d need to figure out how much false positive pollution we’d like to live with. A 100% pollution-free research literature would be nice. So would 100% pollution-free air. However, “100% pollution-free air” is an unrealistic goal. Compliance would be too expensive, and it would come with too many undesirable side effects. Likewise, a research literature that’s 100% free of false positive pollution sounds great, but that’s a goal that cannot be attained without adversely affecting the overall research enterprise. False positives are going to happen—even by scientists who have done their best to avoid them (after all, there is no such thing as a study with 100% statistical power). There must be some amount of false positive pollution we can tolerate.

One way to set an acceptable level of false positive pollution would be to measure the costs and benefits associated with the average false positive emission. How much money is wasted each time a researcher emits an erroneous “finding?” And how much would it cost to prevent such an event? These benefits and costs are likely to vary quite a lot from field to field, so I see good, plentiful work for economists here. In any case, with those data in hand, it should be possible to estimate the optimal amount of false positive pollution that we should be willing to tolerate—that is, the amount that maximizes society-wide benefits relative to costs.

But there’s actually a simpler way to set an acceptable level: Society tacitly endorses the idea that we can live with a 5% false positive pollution rate each time we accept the results of a study in which the p value was set at .05. That’s what p < .05 actually means: “In a world in which the null hypothesis is true, we’d only get results as extreme as those we obtained in this study in 5 out of 100 exact replications.” We could simply make a 5% FPP emissions rate our explicit society-wide ideal.

Step 3: Setting Goals

Once key stakeholders have agreed upon an acceptable annual level, whether that acceptable level is derived by measuring costs and benefits (as outlined above), or by the “5% fiat” approach, an independent regulatory body would be in a position to set goals (with stakeholder input, of course) for reducing the annual FPP emissions rate down to the acceptable level. (In the United States, the regulatory body might be the NIH, the NSF, or some agency that does the regulatory work on behalf of all of the federal agencies that sponsor scientific research; an international regulatory body might resemble the European Union’s Emissions Trading System.)

I’ll illustrate here with a simplified example that assumes a global regulatory agency and a global trading market. Let’s assume that the global production of scientific papers is 1,500,000 papers per year. Now, suppose the goal is to reduce the global false positive emission rate from, say, 50% of all research findings (I use this estimate here merely for argument’s sake; nobody knows what the field-wide FPP emission rate is, though for some journals and sub-fields it could be as high as 80%) to 5%, and we want to accomplish that goal at the rate of 1% per year over a 45-year period. (In our Nature correspondence, space limitations forced Dave and me to envision a move from the current emission levels to 5% emissions in a single year. The scenario I’m presenting here is more complex, but it’s also considerably less draconian.)

Our approach relies on the issuance of false positive pollution (FPP) permits. These permits allow research organizations to emit some false positive pollution, but the number of available permits, and thus, the total amount of pollution emitted annually, is strictly regulated. In Year 1, the Agency would distribute enough FPP permits to cover only 49% of the total global research output (or 1,500,000*.49 = 735,000 false positive permits). The number of permits distributed to each research-producing institution (universities are canonical examples of research-sponsoring institutions, as are drug companies) would be based on each institution’s total research output. Highly productive institutions would get more, and less productive ones would get fewer, but for all institutions, the goal would be to provide them with enough permits to allow a 49% emissions rate in Year 1. After the agency distributes the first year’s supply of FPP permits, it’s up to each individual research-sponsoring institution to determine how it wants to limit its false positive pollution to 49%. In Year 2, the number of permits distributed would go down a little further, a little further in the year after that, and so on until the 5% ideal was reached.

By the way, there are lots of ways to make the distribution process fair to small businesses, independent scientists, and middle-school science fair geniuses (including, for example, exempting small research enterprises and individuals, so long as the absolute value of their contributions to FPP are trivially small) so it’s not fair to dismiss my idea on the basis of such objections. Cap and trade systems can be extremely flexible.

Step 4: Monitoring and Enforcement

Once the FPP permits have been distributed for the year, the regulatory agency would turn to another important task: Monitoring. In the carbon sector, monitoring of individual polluters can be accomplished with electronic sensors at the point of production, so the monitoring can be extremely precise and comprehensive. In the research sector, this level of precision and comprehensiveness would be impossible. We’d have to make do with random samples of research-producing institutions’ research output from the prior year. (Yes; some research studies would be difficult to replicate because the experiment or data set is literally unrepeatable. Complications like these, again, are just details; they don’t render a cap-and-trade approach unworkable by any means). If the estimated FPP emission rate for any research-sponsoring institution substantially exceeded (by some margin of error) the number of FPP permits the institution possessed at the time, the institution would be forced to purchase additional permits from other institutions that had done a better job of getting their FPP emissions under control. If you, as a research institution, could get your FPP emissions rate down to 40% in Year 1, you’d have a bunch of permits available to sell on the market to institutions that hadn’t done enough to get their emissions under control. In a cap and trade system, there is money to be made by institutions that take their own false positive pollution problems seriously.

The Virtues of a Cap and Trade System

Cap and trade systems have many virtues that suit them well to addressing the replication crisis. Here are a few examples:

  • Cap and trade systems use shame effectively. On one hand, they enable us to clearly state what is bad about false positives in a way that reduces righteous indignation, shame-based secrecy, and all of the pathologies these moralistic reactions create. On the other hand, were we to make information about institutions’ sales and purchases of false positive permits publicly available, then institutions would face the reputational consequences that would come from being identified publicly as flagrant polluters. Likewise, permit-sellers would come to be known as organizations whose research was relatively trustworthy. These reputational incentives would motivate all institutions—even Big Pharma and universities with fat endowments, which could afford to buy all the excess permits they desired on the open market—to get their emissions problems under control.
  • Cap and trade systems don’t rely on appeals to personal restraint, which are subject to public goods dilemmas. (Fewer false positives are good for everyone, of course, but I’m best off if I enjoy the benefits of your abstemiousness while I continue polluting whenever I feel like it.) Cap and trade systems do away with these sorts of free-rider problems.
  • Cap and trade systems encourage innovation: Each research-sponsoring institution is free to come up with its own policies for limiting the production of false positives. Inevitably, these innovations will diffuse out to other institutions, increasing cost-effectiveness in the entire sector.
  • A cap and trade system would be less chilling to individual investigators than a simple audit-and-sanction system would be because a cap-and-trade system would require institutions, and not just investigators, to share in the compliance burden. Research-sponsoring institutions take the glory for their scientists’ discoveries (and the overhead); they should also share the responsibility for reform.
  • Most importantly; cap and trade systems reduce pollution where it is cheapest to do so first. All of the low-hanging fruit will be picked in the first year; and harder-to-implement initiatives will be pursued in the successive years. This means that we could expect tangible progress in getting our problems with false positives under control right away. Audit systems do not possess this very desirable feature.

Wouldn’t a Cap and Trade System Be Expensive?

Elizabeth Iorns estimated that it costs $25,000 to replicate a major pre-clinical experiment that involves in vitro and/or animal work. I don’t know that well-conducted laboratory-based behavioral experiments are that much cheaper (at least, once you’ve factored in the personnel time for running the study, analyzing the data properly, and writing up the paper). So all of those replications goal-setting and monitoring purposes are going to cost a lot of money.

But bear in mind, as I already explained, that false positives are expensive, too—and they produce no societal benefit. In fact, what they produce is harm. It costs as much money to produce a false positive as it does to produce a true positive, but the money devoted to producing a false positive is wasted. (If it’s true that the United States spends around $70 billion/year on basic research, then if even 10% of the resultant findings are false positives (which is almost surely a gross underestimate), then the U.S. alone is using $7 billion dollars per year to buy pollution). Also, Tamiflu. What if we used some of the money we’re currently using to buy pollution to make sure that the rest of our research budget is spent not on the production of more pollution, but instead, on true-positives and true-negatives—that is, results that actually have value to society?

Cap and Trade: Something For Everyone (In Congress)

Here’s the final thing I like about the cap-and-trade idea: It has something for both liberals and conservatives. (I presume that enacting a project this big, which would have such a huge impact on how federal research dollars are spent, would require congressional authorization, and possibly the writing of new laws, but perhaps I am wrong about that). Liberals venerate science as a source of guidance for addressing societal problems, so they should be motivated to champion legislation that helps restore science’s damaged reputation. Conservatives, for their part, like market-based solutions, private sector engagement, and cutting fraud, waste, and abuse, so the idea should appeal to them as well. In a congress as impotent as the 113th U.S. congress has been, can you think of another issue that has as much to offer both sides of the aisle?

Solving Science’s False-Positive Problem with a Cap and Trade System: My Letter (w/ Dave Kelly) in Nature

Like many people, I have been reading and thinking quite a lot about the replication crisis in the sciences over the past year. I got together with my economist colleague Dave Kelly to develop a proposal to tackle the replication crisis with a market-based solution. The idea rests on a cap-and-trade system, which has been a successful approach for regulating and reducing many other kinds of pollution (which, at the end of the day, is exactly what false positives are).

Our brief correspondence, linked to here, was published today in Nature.

I am putting the finishing touches on a blog entry in which I explain the idea in much greater detail than Dave and I were able to do in only a few hundred words. I’ll be posting as a separate entry a bit later.