My Intelligently Designed Mouse Pad
Occasionally people ask me why I never write posts about Creationism or Intelligent Design, topics that other evolution-minded bloggers visit with some frequency. The short answer is that while I recognize the importance of teaching students science rather than superstition in schools, the debate seems more or less a waste of time to me, a bit like geologists pounding the table about how the Flat Earthers are wrong. It just doesn’t strike me as something to bother with.
Hey, wanna check out my pad?
On the other hand, someone recently asked me about the mouse pad I’m currently using in my office at school – pictured – so I thought I would take a moment to explain myself. Some time ago, a student gave me the mouse pad pictured here, and I pressed it into service.
As you can see, the mouse pad features a “creation scientist” named Professor Giraffenstein, which right away might strike some as skirting the edge of some vaguely offensive ethnic allusion. More to the point, the mouse pad is supposed to illustrate Michael Behe’s notion of “irreducible complexity,” and it’s this aspect of the mouse pad that brings me much joy.
Behe introduced the notion of irreducible complexity in Darwin’s Black Box, a must read for anyone stranded on a desert island with absolutely nothing else to read. The basic idea of irreducible complexity is as follows. Suppose you have a device that has a number of parts such that if you remove any one of them, the whole thing won’t work. Behe favors the example of a mousetrap to illustrate the point. If you remove the spring or the base, then the mousetrap won’t work, even if all the other parts are still in place. The key point is that the mousetrap doesn’t become a little less good at functioning as a mousetrap without any one of the these two parts; it ceases to function as a mousetrap at all. In his own words, a system is irreducibly complex if it is:
composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning. (p. 39)
Behe suggests that mechanisms that show this property pose a problem for the theory of evolution because it implies that there was no gradual route to the current design. If all parts are simultaneously necessary, then there must have all appeared at the same time as opposed to there being a gradual pathway with the thing working pretty well up until the most recent bit was added on.
An easy way to see a basic problem with this argument is to consider human artifacts such as arches, which will collapse if any of a large number of individual constituent stones are removed. Scaffolding allows such arches to be built; once the scaffolding is removed, the arch has the property that removing any of a large number of pieces will lead to the collapse of the whole thing. Evolutionary scaffolding can bring about the same result.
And here’s what’s great about the little mouse pad propaganda. The thing about a mouse pad is that if you remove a part of it, say one square inch from the corner, it doesn’t cease functioning as a mouse pad. It’s just a little bit worse, yes, but it exactly doesn’t have the property of being irreducibly complex. It works just a little bet worse as you remove bits; it’s reducibly simple, if I may. If one were going to produce an irritating and patronizing example of irreducible complexity, one ought to choose something whose function isn’t gradually eroded as you removed bits of it.
And, you know, not to flog a dead Giraffenstein, but the second quotation on the mouse pad is a bit odd as well. The claim there that GOD designed the human hand so that it could operate a mouse implies that all the other things one can do with a hand are a side-effect of being able to operate a mouse, that the hand’s function is mouse-operation as opposed to a more broad description, manipulating small objects or some such. Not only that, but if the hand is for using a mouse, then why bother with 4th finger and pinky? Unless I’m doing it wrong, I don’t use these two fingers when I use the mouse. Ring finger, well, maybe, but my pinky is essentially useless. If GOD were designing a mouse-using mechanisms, what are those extra digits for? It seems to be a bad design, which ought to lead even ID people to infer that GOD had something else in mind when he made hands
Which brings up a question that I’ve been thinking about recently. Suppose, for argument’s sake, you assumed that some organism was designed by GOD or some other natural or supernatural entity, and that this entity built the different parts of the organism to execute different tasks (such as getting food, using a pointing device, looking beautiful for the benefit of members of other species, etc.). Would it be possible to infer what the different bits of such an organism were for in the sense of the tasks that the Designer intended those bits to perform? Could you use the shape, say, of organisms’ parts to guess the intended function?
Why You Should Stop Waiting For John Horgan to Master the Distinction Between “Ought” and “Is”
In the October 1995 Issue of Scientific American, John Horgan published a piece on the previous summer’s annual meeting of the Human Behavior and Evolution Society (HBES), which had taken place at the University of California Santa Barbara, where I was, at the time, pursing my PhD with Leda Cosmides and John Tooby. (A photo of the pair with a Swiss Army knife graces the second page of the article. It’s actually a nice shot.)
Probably the most obviously incorrect aspect of the piece is the title, “The New Social Darwinists.” Social Darwinism is, of course, a political ideology, a set of ideas about values, or political oughts; HBES is, of course, a scientific society, and presenters at the conferences were making positive claims, about what is. Interestingly, in the body of the piece, Horgan explicitly acknowledges the is/ought barrier, writing of the attendees that “[m]ost shun the naturalistic fallacy, the conflation of what is with what should and must be.” His choice of title might, one could generously suppose, be intended as a play on words of some kind.
Still, a recent piece by Horgan suggests that he still hasn’t quite been able to keep “is” and “ought” distinct. In a blog post at Scientific American, Horgan criticized New York Times columnist David Brooks for looking to some of David Buss’s research in trying to explain the killing of 16 civilians by an American soldier. Horgan writes:
Evolutionary psychology, instead of giving Brooks fresh insights and leading him in unpredictable directions, seems merely to validate his dark, Hobbesian perspective on human affairs. Instead of blaming American war crimes on our killer genes or even “original sin” (yes, Brooks actually invoked that medieval superstition in his column), he should look more closely at political leaders, voters and pundits who have helped turn theU.S.into the world’s most warlike society. This is a cultural problem, not a genetic one.
The use of the word “blaming” carries what to me seems like strong normative connotations, as if the scientific explanation on offer somehow exculpates. In fact, Brooks was using Buss’s findings to try to explain not excuse the alleged massacre, writing that “the real question is not what makes people kill but what prevents them from doing so. People who murder often live in situations that weaken sympathy and restraint.” That is, Brooks was not, to my reading, blaming the alleged crimes on genes, but locating the explanation for them in the details of context. Now, the explanations on offer by Buss and Pinker, the latter of whom Brooks also cites, might be wrong. Indeed, Horgan seems to think that it was only recently that members of our species killed one another in large numbers. Whether or not there are adaptations designed for killing, it seems to me that people ought to be held accountable for murder either way.
A completely separate issue raised in the last sentence I quoted above is Horgan’s insistence on the archaic culture/genetic dichotomy, a confusion that, like his troubles with is and ought, he seems not to have been able to shake in the two decades he’s been trying to talk about evolutionary psychology. In the 1995 Sci Am piece, he mulls a hypothetical audience member listening to the late Dev Singh’s presentation on waist-to-hip ratio: “Surely one of Singh’s several hundred listeners—many of whom are female—will object that his research is offensive, silly or, at any rate, unscientific. Men’s tastes are obviously dictated by culture, someone will argue, rather than by ‘instinct’” (Aside: Singh’s “offensive, silly or unscientific” 1993 JPSP paper on waist to hip ratio has attracted 771 citations to date.)
Similar sorts of patterns are visible in Horgan’s thinking in his somewhat bizarre remarks about David Buss:
First of all, Buss is like a parody of an evolutionary biologist, who spins surveys of modern, mostly American college kids into cartoonishly simplistic proclamations about human evolution. As I noted in an October 1995 article in Scientific American, “The New Social Darwinist,” [sic] Buss’s speculations–which discount the role of nurture, culture and reason in shaping our behavior–are prime examples of what the biologist Stephen Jay Gould mocked as Darwinian “just-so stories.”
Holding aside the tiresome Gouldian trope at the end, his line about “mostly American” college kids is a bit ironic given Horgan’s remark in the 1995 piece (whose title he couldn’t quite render accurately) in which he specifically alludes to Buss’s worldwide research reach. Buss is, in any case, an odd target to choose, and label a “parody” of anything, given his stature and accomplishments, never mind his success in training students who have achieved, or are well on their way to achieving, prominence in the field.
Still, I do think there’s a larger issue here having to do with the is/ought barrier. It doesn’t seem to me that people perceive all “natural” explanations for social phenomena as excusing or justifying those phenomena. After all, non-evolutionary explanations are also intended to be “natural” ones. But it doesn’t seem that social psychological explanations for, say, racial stereotyping – perhaps due to the tendency to use categories to simplify their world, or what have you – elicit the same sense that to have explained the phenomenon justifies or excuses it
To take a more controversial sort of example, consider the explanation for rape that it is due to male desire for power (as opposed to sex). The idea that men want power over women is a natural explanation, and therefore could, in principle, be perceived as justification for rape. In practice, it doesn’t seem to me that it ever is. My experience is that only certain sorts of explanations are viewed as having moral weight and, of course, it seems like explanations that refer to biological functions are frequently so viewed. If that’s true, there’s probably a natural explanation for that, too. But that doesn’t make it OK.
Sex Differences in Jealousy: A New Paper Analyzing a Boatload of Data
Intrasexual competition --> jealousy + tough mate choice
A new paper by Brad Sagarin and colleagues in press in Evolution and Human Behavior addresses a roiling debate among researchers studying jealousy. Sagarin et al. harvested 209 effect sizes from studies investigating jealousy using various techniques to assess whether there is, as some have proposed, a sex difference in jealousy, as well as a number of additional issues swirling around this issue. In case you don’t want to read any further, the answers are: 1) yes, there’s a sex difference as predicted by parental investment theory, 2) no, this difference doesn’t appear only on forced-choice question formats, and 3) no, the difference is not limited to hypothetical infidelities.
Readers of this blog are likely to be familiar with the arguments surrounding jealously from an evolutionary point of view. (If not, don’t be shy about getting a copy David Buss’ book on the topic.) Briefly, the adaptive problem that men face to a greater extent than women in paternity uncertainty. To defend against the possibility that a man’s mate has sex with another man, jealousy, on this account, is designed to deter sexual contact. So men, more than women, should be expected to be more sensitive to, and react more strongly to, the possibility of sexual infidelity in order to implement this deterrence function. By contrast, women face a greater problem of the diversion of investment. To deter a man diverting resources to another woman, the argument goes, women should be expected to be more sensitive to and react more strongly to cues associated with the diversion of resources.
A number of researchers have taken issue with this line of argument, and proposed alternative accounts. For example, DeSteno et al (2006) published a paper in the Journal of Personality and Social Psychology in which they suggested that “little empirical evidence exists that provides strong support for a specific model of jealousy,” and that “the previously prevailing view that jealousy stems from sex-specific, evolved modules sensitive to reproductive threats (see Buss et al., 1992) has encountered formidable theoretical and empirical difficulties that limit its viability.” (I’m not in a position to judge the former claim, since I’m not sure how much evidence would count as more than just a little; as for the theoretical and empirical difficulties, I (and my colleagues) are skeptical of the sort of arguments that DeSteno and his colleagues level against the evolutionary account.)
We all know what's she's thinking... ("My self is threatened!")
In any case, presumably in part because of their worry about this supposed viability limit, DeSteno et al. propose an alternative perspective, locating the issue not in the threat to paternity certainty or parental investment, but in a perennially favored “explanation” in social psychology, self esteem, writing (citations omitted):
…it is our contention that threatened self-esteem is the principal mediating mechanism of jealousy…Our central point is that the appraisal centers on the self-system, and variations in momentary levels of self-esteem stand as the driving force for jealousy (p. 628)
With respect to jealousy, the role played by self-evaluation may be quite specific. Given that the attention one receives from a partner in a valued relationship is usually taken to signify self-worth, a partner’s interest in a rival stands as a signal that the rival is superior in some way to the self, and, consequently, the integrity of the present relationship may be threatened by the value the partner places on the rival… (p. 628) Put simply, maximizing self-esteem derived from the views of relationship partners safeguards the more tangible resources stemming from these relationships (p. 629).
I’ve written elsewhere about my views on theories that point to the “desire to feel good about the self” as a psychological explanation, and I won’t belabor the point here, except to say that I am actually fairly confident that self-esteem as the key explanatory variable for understanding jealousy will do about as well as it has in other contexts. (On the other hand, this idea does help to explain why men so frequently tell their romantic partners, sure, go ahead and have sex with him, just as long as you don’t place more value on him than me…)
In any case, Sagarin et al. address two critiques raised in the context of the jealously literature. The first surrounds measurement, with the claim being that the sex difference – men showing more jealously to sexual infidelity compared to women – occurs in forced choice methods (i.e., indicate which would make you more jealous, sexual or emotional infidelity) but not continuous methods. The second critique is a worry that the sex difference appears in hypothetical dilemmas (i.e., in such a case, how would you feel?) as opposed to actual cases.
Sagarin et al. spend some room in the paper laying out what predictions the evolutionary argument makes, and although this material is worth a careful read, I won’t review it here. Briefly, they argue that the key issue is the interaction term, that men should show a bigger difference than women show in their responding to sexual versus emotional infidelity. They also have a nice discussion of how one ought to treat Likert scale data, and I like one passage in the paper on this topic (p. 5):
[I]f we are unwilling to make any assumptions about response scales that go beyond ordinality, nearly every parametric test performed on nearly every response scale used in psychological research is essentially uninterpretable. This would include vast quantities of psychological research, including all attitudes research that used Likert and semantic differential scales, all personality research that used standard response scales to measure self-esteem, the Big 5, self monitoring, and other individual difference constructs, all emotion research that used the Positive and Negative Affect Scale (PANAS) and similar instruments to assess affect, and so on. This seems to be a lot to sacrifice at the altar of a measurement taxonomy.
The main contribution of the paper, however, is the meta-analysis, which consisted of analyzing 199 effect sizes drawn from 47 independent samples. Summarizing their findings regarding the key issue of continuous measures, they write: “One of the clearest findings in the meta-analyses is the existence of a sex difference in negative emotional responses to hypothetical infidelity scenarios using continuous measures” (p. 15). In terms of the issue of actual versus hypothetical infidelity, there are, as one might expect given the methodological challenges, fewer studies that investigate actual infidelity but, still, Sagarin et al. write:
Across the seven independent samples that measured responses to actual infidelity experiences, a significant, theory-supportive effect emerged (g*=0.234, 95% CI [0.020, 0.448], p=.03) with three individual effects statistically significant, all in the theory-supportive direction. Moreover, from a statistical perspective, the data yielded by these studies is not substantially different from the data yielded by the studies that have assessed jealousy responses to hypothetical scenarios, lending credence to the results that have emerged from both types of studies.
An additional result of their analysis is that it matters a great deal which emotion researchers ask subjects about. As one might expect, the effects are strongest when subjects indicate their level of jealousy, while for other emotions – anger, disgust – the effects are smaller. They conclude that “the choice of emotion measured helps to explain the diversity of past findings, with studies that measured distress/upset and jealousy producing significantly larger effects than studies that measured other emotions” (p. 15).
Sagarin et al also looked at variables that moderate these effects, and identify a small number of them, including the use of student samples and some methodological choices, such as whether the study was conducted on a computer.
The controversy surrounding jealousy is unlikely to be settled by the present paper, but by brining together the large number of studies in this way, Sagarin et al have provided an important analysis that researchers in this area will have to address as different models of jealousy are evaluated.
References
Buss, D. M. (2000). The dangerous passion: Why jealousy is as necessary as love and sex. New York: Free Press.
DeSteno, D., Valdesolo, P., & Bartlett, M. Y. (2006). Jealousy and the threatened self: Getting to the heart of the green-eyed monster. Journal of Personality and Social Psychology, 91, 626–641.
Postscript: People sometimes ask me about the turnaround time at Evolution and Human Behavior. This paper was submitted on January 5th, underwent one round of revisions, was accepted on February 28th, and published online on the 11th of May. This speed is not necessarily typical, but the editors at E&HB are very conscious of the issue of turnaround time, especially between submission and initial decision.
Some NEScent Announcements
Gillian Bentley (Anthropology, Durham University) asked me to post the following brief announcement:
As part of a NEScent-funded working group ‘Infusing Evolutionary Thinking into Medical Education’, we are looking for people with a PhD in human biology with good training in evolutionary thinking who are now practicing Physicians or training to be one.
If you know of such PhDs or other graduate students who went off to med school, please ask them to email one of us (a.read@psu.edu or g.r.bentley@durham.ac.uk). If you have lost contact, please email us their name and any contact details as you have (which medical school, when?), and we’ll try to track them down. We are interested in all ages, all countries, and any area of evolutionarily-oriented studies.
At this point we just want to discuss our working group topic with medical trainees and professionals who have advanced evolutionary research training. But we might also try to grow this into an ongoing network to further broader professional interests.
And here are some additional NESCent announcements that I thought I would pass along:
POSTDOCTORAL FELLOWSHIPS IN EVOLUTIONARY BIOLOGY AND RELATED FIELDS
We are now accepting proposals for Postdoctoral Fellowships at The National Evolutionary Synthesis Center (NESCent). We are looking to support innovative approaches to outstanding problems in evolutionary science. Proposals in any area of evolutionary science are welcome, but proposals in the following areas are of particular interest: Evolutionary Medicine, Synthetic Biology and Origins of Life, Evolution and the Social Sciences, and K-12 Minority Education in Evolution. Proposals are due July 10 for two-year Fellowships that will begin no later than January 2013; we anticipate that award decisions will be made by first week of October. For more information, please see our website at https://www.nescent.org/
CALL FOR PROPOSALS – SABBATICAL SCHOLARS, WORKING GROUPS AND CATALYSIS MEETINGS
Proposals for Sabbaticals, Working Groups and Catalysis Meetings are now being accepted at The National Evolutionary Synthesis Center (NESCent). We are looking to support innovative approaches to outstanding problems in evolutionary science. In particular, proposals that have a clear interdisciplinary focus, or involve evolutionary concepts in non-traditional disciplines, are strongly encouraged, as are proposals that demonstrate international participation and a mix of senior and emerging researchers, including graduate students. Proposals are accepted twice a year, with deadlines on July 10 and December 1. Proposals in any area of evolutionary science are welcome, but proposals in Evolution and the Social Sciences and K-12 Minority Education in Evolution are also being considered for the July 10 deadline (Proposals in one of these two areas must include “Targeted Initiative” in proposal title; see also http://www.nescent.org/news/
GRADUATE FELLOWSHIPS IN EVOLUTIONARY SCIENCE AND RELATED FIELDS
NESCent is now including graduate training in its portfolio, by offering one-semester fellowships for graduate students to pursue research with a NESCent sabbatical scholar, a NESCent postdoctoral scholar, or a NESCent Working Group. Deadlines are January 1 (for a fall semester fellowship) and July 1 (for a spring semester fellowship). For more information, please see our website at https://www.nescent.org/
Evolutionary Explanations for Altruism and Morality: Some Key Distinctions
Last Thursday-Saturday, I attended a Workshop entitled Positive Models and Normative Ideals of Social Cooperation at Princeton University. I was asked to write a précis for the workshop on the evolution of altruism and morality. I assumed as I wrote it that the short piece would be read by people with a diversity of backgrounds, and so I tried to keep things relatively simple. The organizers of the workshop don’t intend to publish the set of pieces written for it, so I thought I would just post it here, slightly edited from the original. Other papers, including two from Steve Pinker, with whom I shared the first session, all also available on the page I linked to above.
My goals for this brief essay are necessarily modest. First, I discuss some key distinctions surrounding the phenomena one might try to explain with respect to altruism, cooperation, and morality. Second, I discuss some candidate explanations for these phenomena. Note that the presentation here is not intended to veridically represent the views of all practitioners in the relevant fields; it should be understood that this area remains controversial, and there are a diversity of views.
Key Distinctions
Altruism Devices.
Here are three different questions that one might ask surrounding altruism:
- Phenotypic design. Why are organisms’ parts organized to deliver benefits to other organisms?
- Psychology & Phenomenology. Why do organisms (feel, to themselves, or appear, to others, as though they) choose to deliver benefits to other organisms?
- Observed behavior. Why do organisms occasionally act in ways such that they benefit other organisms at a cost to themselves?
Figure 1. A fish endures a net lifetime fitness cost; a bear reaps a net lifetime fitness gain.
Distinguishing these questions directs attention to different sorts of phenomena and different sorts of explanations. Consider the well-known photograph of an upstream-swimming salmon flopping into the open jaws of a waiting bear (Figure 1). In this transaction, the fish has endured a fitness cost (death) and the bear has benefited (calories), an act of “altruism” when altruism is defined in terms of the behavior (as in question 3). However, no part of salmon physiology is designed for bear-feeding (as in question 1). (To put it another way, the genes that cause the salmon to swim upstream in the way that salmon do did not replicate faster than alternative alleles by virtue of their having caused their owners to be eaten by bears.)
In contrast, mammary glands located in female bears are altruism devices. They can be recognized as such because these tissues are organized in such a way that they elegantly execute their function of delivering calories to offspring (Williams, 1964). They contain highly nutritious solutions and tubes that extend from reservoirs of this solution to the exterior world to afford efficient delivery to suckling offspring. Altruism devices can be recognized by investigating their properties and relating these properties to a putative benefit-delivery function.
Benefit-delivery mechanisms can evolve through diverse pathways. Recently, Hansen et al. (2012) showed that distinctive triangular white markings on the petals of irises function to guide the proboscis of insects so that these insects could accurately position themselves to obtain the nectar within the flower; this design is favored because by delivering this benefit to insects, pollination is facilitated. (I wrote a little post about this.)
Humans, of course, are biologically striking in the array of benefits they confer on other humans. Given the above distinctions – and bearing in mind Adam Smith’s admonition regarding butchers and brewers – not all acts that result in benefits to others necessarily entail that such acts are produced by altruism devices. They might be, but such issues must be arbitrated empirically.
Still, the human mind does, as an empirical matter, appear to contain altruism mechanisms. Humans deliver benefits to close relatives (Burnstein et al., 1994), and humans form “friendships,” characterized by the delivery of benefits of various sorts, a robust phenomenon which points to the existence of altruism mechanisms (Silk, 2004). Perhaps most strikingly, humans endure costs to deliver benefits to others, as in “group” activities such as barn raisings and warfare. Candidate explanations for these behaviors are reviewed briefly below.
Moral Devices & Punishment.
Historically, benefit delivery by humans and “morality” have been blurred;Darwinidentified the question of why people cooperate with the question of why people are “moral” or “virtuous.” Here I distinguish between these two phenomena, leaving as an open possibility that they are tightly related to one another.
Most organisms show little interest in acts by conspecifics that don’t affect them. In sharp contrast, humans identify others’ acts as “wrong,” and reliably indicate a desire that costs be imposed on those who commit such acts; this is the case for unrelated individuals, even those in other groups, and the desire for punishments extends even to acts that do not, in themselves, do anyone any harm (e.g., using prohibited words). Some take this as the central puzzle of morality: why do people evaluate acts on the right/wrong dimension, and why is there an accompanying desire for the imposition of costs (i.e., punishment)?
This raises another key distinction which can be expressed with two additional questions:
4) Revenge. What is the function of a (putative) psychological mechanism designed to impose costs on organisms who recently imposed costs on (or refused to benefit) them?
5) Moralistic Aggression. What is the function of a (putative) psychological mechanism designed to impose costs on individuals who committed a “wrongful” act?
In the non-human animal world, revenge is common, and a typical interpretation of observations of vengeful behavior is deterrence (Clutton-Brock & Parker, 1995). To the extent that an organism signals that it will impose costs on another organism conditional on harm to itself, harm is deterred (McCullough et al., in press).
In contrast, third-party punishment, or moralistic aggression, is rare among non-human animals. This is not to say that it is absent; for instance, von Rohr et al. (2012) recently proposed that chimpanzees occasionally intervene as “impartial” third parties in conflicts.
A final distinction surrounding morality can be captured with an additional question:
6) Conscience. Why do human minds have (putative) psychological mechanisms that cause them, ceteris paribus, to avoid engaging in norm-violating behavior?
From these distinctions, it should be clear that one can ask both why the mind is designed to deliver benefits and also ask why the mind is designed to follow moral norms.
Are Moral Devices Altruism Devices?
What are the relationships among these questions? One prominent view is that moralistic aggression (5) helps to explain altruism in groups in humans. Because this idea is the specialty of another workshop participant (Boyd & Richerson, 1992, 2005), I will not discuss this in any depth.
It should be clear that an explanation for moralistic aggression (5) has the appealing property that such an explanation will naturally illuminate conscience (6). That is, once we have explained why humans impose costs on those who commit “wrongful” acts, then we should simultaneously be able to explain why people choose not to commit such acts: because doing them will lead to punishment. That is, conscience mechanisms, psychological systems that cause people to avoid moralized acts, can be understood as defense systems in a social ecology that includes moralistic aggression (DeScioli & Kurzban, 2009).
While these distinctions seem very straightforward, it is important to note that the scholarly literature at the intersection of evolution and morality occasionally blurs the lines between these questions. Following Darwin, contemporary researchers have suggested that the explanation for morality are explanations for altruism (Wright, 1994). Similarly, Haidt and colleagues (e.g., Haidt & Joseph, 2008) understand questions surrounding the evolution of morality to be answered by explanations for why people choose certain behaviors over others, theories about conscience; such explanations do not in themselves address moralistic aggression, implicitly assuming that the explanations for conscience and moralistic aggression are the same.
Explanations
Volumes have been written on explanations for morality and altruism among humans, so this short précis necessarily provides only the most superficial account of these explanations.
Altruism Devices.
Kin selection (Hamilton, 1964) explains why some features of organisms are designed to deliver benefits to other organisms. This theory explains, specifically, why organisms have design features that cause them to deliver benefits at a cost to organisms closely related by descent. The theory of kin selection explains the structure of mammary glands, for example.
Reciprocal altruism (Trivers, 1971) is a second well-known theory that explains how organisms can come to be designed to deliver benefits to others. This theory explains how organisms can come to have mechanisms designed to deliver benefits to other organisms if, over the evolutionary history of the organism in question, certain conditions were met. In particular, such benefit delivery systems can persist if the delivery of benefits reliably led to return benefits. Some have argued that the human mind contains mechanisms selected by virtue of reciprocal altruism (Cosmides & Tooby, 1992); some have proposed that friendship psychology, for example, is a manifestation of the effects of reciprocal altruism (Shackelford & Buss, 1996).
Costly signaling has been proposed as another possibility. This model begins with the idea that people choose others as mates, exchange partners, and allies based on visible cues that provide information about their properties and, therefore, their value as partners in these domains. Drawing on costly signaling theory, (Grafen, 1990; Zahavi, 1975), some authors have suggested that there has been selection for the inclination to deliver benefits to others because displays of altruism are difficult to fake (Gintis et al., 2001; Roberts, 1998) and, therefore, provide reliable information about the altruist. In particular, the ability to deliver large benefits (at large costs) honestly signals the ability to do so, insofar as those with little to give are unable to do so. This view locates the return benefit to delivering benefits to others in the gains that are derived from winning competitions over the choice of partners across a range of social domains.
Recently, indirect reciprocity has been proposed as an additional pathway to altruism mechanisms in sizable groups (Nowak & Sigmund, 2005; Panchanathan & Boyd, 2004). Put roughly and briefly, in these models, individuals with a reputation as cooperators – having behaved altruistically at time 1 – are aided by other agents who only help those with such reputations at time 2. In this way, agents who are altruistic at time 1, maintaining a good reputation, enjoy greater fitness than those who do not, leading to selection for altruism even though the return benefits are not direct, as in reciprocal altruism.
Two final explanations are genetic group selection and cultural group selection. The former explanation relies on the same logic as kin selection, above; a given allele increases its own replication rate by virtue of the fact that groups with more (genetic) altruists will do better than groups with fewer genetic altruists, leading to between-group selection for the altruism gene. The latter explanation, cultural group selection, refers to a process by which groups with certain beliefs (memes, institutions, etc.) do better than other groups because of their positive effect on the success of the group. At the risk of over-generalizing, and with some notable exceptions (e.g., E. O. Wilson, 2012; D. S. Wilson & Sober, 1999), most scholars remain unconvinced that genetic group selection has been an important force in giving rise to human altruism devices. In contrast, cultural group selection enjoys considerably broader support.
Morality Devices.
As indicated above, some have suggested a tight link between altruism devices and morality devices. These views suggest that people’s interest in punishing others is driven by the role that punishment plays in eliciting altruistic behavior. That is, the function of the desire to punish, on such views, is to increase others’ degree of cooperation. The advantage of punishment derives from the increased altruism elicited by others. This solution immediately points to the well-known second order problem of free riding on others’ punishment, a challenge which has been addressed by a number of models (e.g., Henrich & Boyd, 2001). In slight contract, and controversially, Price et al. (2002) have proposed that the desire to punish functions not only to induce cooperation from others, but also to reduce the difference between the punisher’s fitness and the fitness of those that are punished.
A puzzling feature of moralistic punishment is that people punish an array of acts that go well beyond acts that are uncooperative. Punished acts across cultures and eras have included not just those that harm no one – combining particular categories of food, for instance – but even acts that, if performed, would give rise to aggregate benefits (such as charging interest on loans). (See Haidt & Joseph, 2008, for one discussion of diversity in moral rules.)
While it is of course possible that moralistic punishment systems are designed to induce pro-social behavior and are simply “misfiring” as a result of cultural processes (e.g., Hagen & Hammerstein, 2006), recently DeScioli and Kurzban (2009, in press) have proposed a different route. They propose that moral condemnation is designed to choose sides when conflicts arise within a group.
DeScioli and Kurzban (in press) assume that conflicts arose frequently in groups, and that conflicts posed a problem for third parties observing the conflict. In many species, when such conflicts arise, observers side with the dominant, leading to a dictatorship. In humans, however, people do not always side with the more dominant individual (cf. Boehm, 1999). Instead, people frequently will use the behavior of the acts in question (as opposed to the formidability or status of the disputants) to choose which disputant to back. When all third parties to a conflict use the same decision rule to choose sides, these third parties can minimize their costs because all conflicts will be settled with a highly asymmetrical contest.
Choosing sides based on actions changes the problem from a public goods problem to a coordination problem in which agents are better off choosing based on actions rather than formidability (or pre-existing ties). For this reason, DeScioli and Kurzban (in press) consider morality to be best understood as a “dynamic coordination” strategy, in which third parties use the acts of the disputants to choose sides. On this view, moral judgment is designed to pick out the individual that others will side with, and moralistic punishment intuitions are designed to signal to other third parties which side one is taking, a view that connects to recent models that emphasize the role of coordination among third parties (Boyd et al., 2010).
Summary
Debate continues about the function of human morality and the relationship between moral systems and altruism systems. While historically some have regarded the two as equivalent, others have proposed that they are distinct, but functionally related to one another.
References
Boehm, C. (1999). Hierarchy in the forest.Cambridge,MA:HarvardUniversity Press.
Boyd, R., Gintis, H. & Bowles, S. (2010) Coordinated punishment of defectors sustains cooperation and can proliferate when rare. Science, 328, 617–20.
Burnstein, E., Crandall, C., & Kitayama, S. (1994). Some neo-Darwinian decision rules for altruism: Weighting cues for inclusive fitness as a function of the biological importance of the decision. Journal of Personality and Social Psychology, 67, 773-789.
Bliege Bird, R., E. A. Smith, & Bird, D. W. (2001) The hunting handicap: costly signaling in male foraging strategies. Behavioral Ecology and Sociobiology, 50, 9-19.
Boyd, R. and Richerson, P. J. (1992). Punishment allows the evolution of cooperation (or anything else) in sizable groups. Ethology and Sociobiology 13, 171-95.
Boyd, R., & Richerson, P. J. (2005). Not by genes alone: How culture transformed human evolution.University ofChicago Press.
Clutton-Brock, T. H., & Parker, G. A. (1995). Punishment in animal societies. Nature, 373, 209-216.
Cosmides, L. & Tooby, J. (1992). Cognitive adaptations for social exchange. In J. Barkow, L. Cosmides, & J. Tooby (Eds.), The adapted mind: Evolutionary psychology and the generation of culture.New York:OxfordUniversity Press.
DeScioli, P., & Kurzban, R. (2009). Mysteries of morality. Cognition, 112, 281-299.
DeScioli, P., & Kurzban, R. (in press). A solution to the mysteries of morality. Psychological Bulletin.
Gintis, H., Smith, E. A., & Bowles, S. (2001). Costly signaling and cooperation. Journal of Theoretical Biology, 213, 103-119.
Grafen, A. (1990). Biological signals as handicaps. Journal of Theoretical Biology, 144, 517-54.
Haidt, J., & Joseph, C. (2008). The moral mind: How five sets of innate intuitions guide the development of many culture-specific virtues, and perhaps even modules. In P. Carruthers, S. Laurence, & S. Stich (Eds.), The innate mind, volume 3. (pp. 367-391).New York:OxfordUniversity Press.
Hagen, E. H., & Hammerstein, P. (2006). Game theory and human evolution: a critique of some recent interpretations of experimental games. Theoretical Population Biology 69, 339–48.
Hamilton, W. D. (1964). The genetic evolution of social behavior. Journal of Theoretical Biology, 7, 1-52.
Hansen, D. M., Van der Niet, T., & Johnson, S. D. (2012). Floral signposts: testing the significance of visual ‘nectar guides’ for pollinator behaviour and plant fitness. Proceedings of the Royal Society – B, 279, 634-639.
Henrich, J. & Boyd, R. (2001) Why people punish defectors: Weak conformist transmission can stabilize costly enforcement of norms in cooperative dilemmas. Journal of Theoretical Biology (208):79–89.
McCullough, M. E., Kurzban, R., & Tabak, B. A. (in press). Cognitive systems for revenge and forgiveness. Behavior & Brain Sciences.
Nowak, M., & Sigmund, K. (2005) Evolution of indirect reciprocity. Nature, 437, 1291–1298. Panchanathan & Boyd, 2004
Price, M. E., Cosmides, L., & Tooby, J. (2002). Punitive sentiment as an anti-free rider psychological device. Evolution and Human Behavior, 23, 203-231.
Roberts, G. (1998). Competitive altruism: From reciprocity to the handicap principle. Proceedings of the Royal Society B, 265, 427-31.
Shackelford,T .K.,& Buss, D. M. (1996). Betrayal in mateships, friendships, and coalitions. Personality and Social Psychology Bulletin, 22, 1151–1164.
Silk, J. B. (2003). Cooperation without counting: the puzzle of friendship. In: The Genetic and Cultural Evolution of Cooperation (P. Hammerstein, ed.), Dahlem Workshop Report 90.Cambridge,MA, The MIT Press, pp. 37-54.
Trivers, R. L. (1971). The evolution of reciprocal altruism. Quarterly Review of Biology, 46, 35-57.
Williams, G. C. (1966). Adaptation and natural selection. Princeton:PrincetonUniversity Press.
Sober, E. & Wilson, D. S. (1998). Unto others: The evolution and psychology of unselfish behavior.Cambridge,MA:HarvardUniversity Press.
von Rohr C. R. , Koski S. E. , Burkart J. M., Caws C., Fraser O.N., et al. (2012). Impartial third-party interventions in captive chimpanzees: A reflection of community concern. PLoS ONE 7(3): e32494.
Wilson, E. O. (2012). The social conquest of Earth.New York: Liveright.
Wright, R. (1994). The moral animal.London: Little Brown.
Zahavi, A. (1975). Mate selection—A selection for a handicap. Journal of Theoretical Biology, 53, 205-214.
The Awful Green Things From Outer Space and Experimental Design
When I was young – and readers might find this difficult to believe – I was pretty geeky. When I wasn’t watching Star Trek or reading Isaac Asimov novels, I was not infrequently playing some board game or other with my similar-minded friends.
This is, in fact, going somewhere, though, full disclosure, this post has little to do with evolutionary psychology.
The Znutar
Anyway, one board game that I liked was called “The Awful Green Things From Outer Space.” The game took place on a spaceship, the Znutar (pictured here in a fantastic 3D production) which was invaded by, as the name of the game suggests, Awful Green Things. The AGTs had a three-phase life cycle, growing from eggs to juveniles to adults; adults were tough, bipedal one-eyed heavies.
The crew of the Znutar (which consisted of Snudalians, Smbalites, Frathms and Redundans) could attack the AGTs unarmed but, really, the AGTs were too strong for the crew, generally, to take on mano-a-mano. So, the crew could also pick up various artifacts to use as weapons. This could include cans of Zgwortz (the crew’s source of food), welding torches, a fire extinguisher, and so on. The problem was that because the biology of the AGTs was unknown, it was impossible to foresee the effect that a given weapon might have on the invaders. So, whenever a crewmember used a weapon for the first time, the player had to draw from a random set of effects that the weapon could have. The weapon might harm the green thing, have no effect, or even benefit the green thing, though thankfully for the crew this was unlikely. The fact that weapons had randomly assigned effects meant that the game was different each time one played.
Members of the crew in an Awful predicament
It also meant that to find effective weapons, you had to run experiments. So, suppose you’re the crew player, and you have crew member Sparks use the fire extinguisher on a room of Awful Green Things. You draw one of the chits from the pile, and discover that the fire extinguisher Shrinks the AGTs one life history phase. Great! A useful weapon. You have learned something valuable that will be true for the duration of the game. Every time you use the fire extinguisher in the future (again, in this particular instance of the game) the fire extinguisher will Shrink any Awful Green Thing on whom it is used. (Adults become juveniles, juveniles become eggs, eggs become poached. No, seriously, the eggs just die.)
However, now suppose that two of your crew members gang up on an Awful Green Thing with previously untried weapons. One uses the fire extinguisher on it, and the other throws a can of Zgwortz at it. Now you draw a chit from the pile, and you learn the effect of both attacks, jointly, on the Awful Green Thing.
Here is the problem. As an empirical matter, all you now know is what these two weapons do jointly. You don’t know what the fire extinguisher, by itself, does and you don’t know what the can of Zgwortz, by itself, does. If you use either one again in the future, by itself, you have to draw a chit to determine its effect. By using both at the same time, you have learned nothing about what each one does, individually. Your experiment might have been useful for this one attack on the Green Thing, but you haven’t learned anything useful about each artifact by itself.
And that is how, though I didn’t know it at the time, Tom Wham and Steve Jackson introduced me to the idea of the problem of introducing experimental confounds into a design, to say nothing of the problem of interpreting main effects when you have a significant interaction term.
Long live the crew of the Znutar!
Strong Fear
What is fear? Roughly, fear is an emotion designed to motivate appropriate behavior, especially escape, when faced with a threat such as a predator or enemy. The explanation for the emotion of fear, then, lies in the fitness benefits of avoiding being killed by enemies or predators and such like. People who got scared and so fled from charging velociraptors left more offspring, on average, than those who didn’t.
Strong Mirth?
Now, as an empirical matter, humans do not show fear responses only to those things that can, in fact, harm them. Take, for instance, the movie Hugo, adored by critics and The People (though I found watching it, frankly, a bit misérable); consider the scene in which a small audience is watching a moving image of an approaching train. The viewers scramble out of the way of the image of the train, even though they know that there is no actual train about to hit them. It appears to come hurtling toward them, and they flee from this appearance. From this and our other everyday experiences, we know that, empirically, humans show fear responses not only to any number of stimuli that can’t hurt them, but also to stimuli that the people who are fearful know, for sure, can’t hurt them.
So, we might now say that there are two distinguishable phenomena. The first is garden variety fear, which is something like being afraid and having the propensity to flee when there is something in the world that, as a matter of fact, actually poses a threat; the (ultimate) explanation for this “garden variety fear” is the one I indicated above, the fitness benefits of avoiding being killed. Such individuals are just regular “fearful.”
However, movies of trains are not, on this way of speaking, garden variety. We’ll call cases in which people show fear when they can’t, in fact, be harmed by stimuli that only appear to be dangerous as “Strong Fear.” We might put it this way:
Fear, as it is used in evolutionary psychology, differs from Strong Fear because a Garden Variety Fearful individual is only afraid if there are actual benefits from being afraid. Thus, a Fearful individual will never show fear to artificially scary stimuli. In contrast, a person who is Strongly Fearful will be afraid of scary stimuli even when there are no actual benefits from being afraid, and even if the person knows that there are no such benefits.
This might strike some readers as a bit loopy. However, the structure of the argument above is no different from the structure of the argument made in the service of distinguishing Reciprocity from Strong Reciprocity:
Reciprocal altruism, as it is frequently used in evolutionary biology, also differs fundamentally from strong reciprocity because a reciprocal altruist only cooperates if there are future returns from cooperation. Thus a reciprocally altruistic player B will always defect in a sequential one-shot PD. (Fehr et al., 2002, p. 4)
In the quotation directly above, a distinction is being drawn between a garden variety reciprocally altruistic individual – they reciprocate only when there are actual potential downstream benefits – and a strongly reciprocal individual, who, just like the Strongly Fearful individual, will reciprocate even when there are no actual benefits from being reciprocal and knows that there are no such benefits. (Compare this sentence to the parallel sentence above. And we can argue about the claim about the conditions under which reciprocal altruists should be expected to cooperate – which is an important point but also not relevant to my present point – which is only about the distinction being made.)
Once we have this distinction, we can begin to try to explain the empirical phenomenon of Strong Fear. Here are two different explanations. One is the “mismatch” or “big mistake” explanation. This view is familiar to students of evolutionary psychology. Stimuli that match the input conditions of evolved systems evoke the responses for which these systems evolved, even if the link between the stimuli and the reason they were selected has been broken in modern environments. (See, for instance, Hagen & Hammerstein, 2006). In the past percepts of looming predators reliably correlated with the presence of a looming predator. In modern environments, looming predators can be simulated, breaking this reliable correlation.
Here’s a second sort of explanation. Perhaps there was some reproductive advantage to fleeing from simulacra of things that could cause harm. Again, some readers might find this to be an unusual sort of argument, but again I propose it as a parallel to one actually on offer. Using a similar rhetorical riff to the one I’m favoring here, Price et al. (2007) pointed to the consumption of pornography, a pattern of (unbelievably popular) behavior that carries no obvious benefits. Gintis, replying to this example, wrote that: “the capacity to be motivated by artificial visual material may well be an adaptation.” This explanation is that there were fitness advantages of some type to being motivated by artificial stimuli; getting turned on by porn, according to this view, is functional. Again, the analogous argument here would be that there was some fitness advantage to being afraid of images of things that actually couldn’t hurt the viewer, that people who fled from safe but scary-looking things (somehow) out-reproduced people who did not.
Now, I find this explanation implausible on the face of it, but it is an explanation, though one would want to know what fitness benefits Gintis has in mind when he envisions the advantages to being aroused by pornography.
Of course, these two explanations do not exhaust the range of possible explanations. Perhaps there was some group-wide benefit to people fleeing from images of trains that that led to a between-group selection pressure that more than countered the individual costly behavior of uselessly fleeing harmless stimuli, for example.
In any case, whatever the explanation for Strong Fear, it’s important to bear in mind that the term refers to a phenomenon, a set of observations that people show fear reactions to stimuli that can’t, as a matter of fact, harm them. It is not itself an explanation for anything. Referring to Strong Fear as a model or an explanation for some other set of behaviors would be a mistake (perhaps a “Big Mistake”), confusing the thing to be explained with the explanation for it.
(Left to the student: fear is considered something of an aversive state, yet people spend half a billion dollars to see horror movies. Discuss.)
(Hat tip: Mike McCullough)
References
Fehr, E., Fischbacher, U., & Gächter, S. (2002). Strong reciprocity, human cooperation and the enforcement of social norms. Human Nature, 13, 1–25
Gintis, H. (2007). Unifying the behavioral sciences II. Behavioral and Brain Sciences, 30, 45-53.
Hagen, E. H., & Hammerstein, P. (2006). Game theory and human evolution: A critique of some recent interpretations of experimental games. Theoretical Population Biology, 69, 339-348.
Price, M. E., Brown, W. M., & Curry, O. S. (2007). The integrative framework for the behavioural sciences has already been discovered, and it is the adaptationist approach. Behavioral and Brain Sciences, 30, 39-40.
Further Reading
Burnham, T., & Phelan, J. (2000). Mean genes: From sex to money to food: Taming our primal instincts. New York, NY: Perseus.
The Red Queen & Red (and Green and Blue) Eggs
The problem, if you are an African tawny-flanked prinia (Prinia subflava), is that the cuckoo finch (Anomalospiza imberbis) is designed to lay its eggs in your nest, fooling you into investing in the finch’s offspring at the expense of your own. To defend against this, it’s helpful to have eggs that are distinctive; if you laid only plain white eggs, parasites would similarly lay plain white eggs, making distinguishing yours from theirs difficult.
This doesn’t solve the problem. Once there has been selection for distinctive eggs, there is selection on the finches to produce eggs that are similar to the predominant color and pattern of the eggs in a given prinia population, leading, in turn, to selection on prinias to produce eggs different from the sorts of eggs that the finches are now producing. The advantage of laying eggs that deviate from other’s eggs can produce a co-evolutionary race in which prinia egg color patterns are being selected to run away from the pattern finches are producing, with the cuckoo egg patterns in pursuit.
This evolutionary dynamic is the study of a new paper by Claire N. Spottiswoode and Martin Stevens entitled, “Host-Parasite Arms Races and Rapid Changes in Bird Egg Appearance.” They had access to a number of eggs from the host species, collected between 2007 and 2009, as well as eggs collected in the past, mostly the 70’s and 80’s. They were, then, able to compare these two groups of eggs with eggs from the brood parasite species. Based on the ideas above, they made three predictions:
Our first prediction is that phenotypic diversity in egg appearance should have changed over time in both parties, as host phenotypes diversify or contract under negative frequency-dependent selection and parasitic phenotypes follow. Different aspects of egg appearance may oscillate over time in phenotypic space…
…our second prediction is that if parasite evolution is closely tracking host evolution, then parasitic eggs should be a better phenotypic match to host eggs from the same time period than to host eggs from a different period. We further predict that the latter effect should be most pronounced when comparing historical host eggs to current-day parasites that hosts have not yet encountered in their evolutionary history; in contrast, a smaller effect might be expected when comparing current-day hosts to historical parasites, which have previously imposed selection on the host population.
Finally, we predict that parasites should show less phenotypic diversity than hosts, owing to a time lag between host and parasite adaptation.
So, in sum, they predict changes in appearance, a closer match between modern host eggs than to prior host eggs, and more variation in host eggs.
Eggcellent colors.
The eggs, it should be said, are pretty cool looking. See Figure 1. The authors used what is known about the avian visual system to quantify the visual properties of the eggs (since what matters is how much eggs resemble one another from the point of the view of the birds, not from the point of view of people, of course). From these calculations, they could quantify how different eggs appeared to be from one another.
Their predictions fared well. Modern host eggs were more variable than the eggs from prior decades, by more than a factor of five, by one of their metrics. The results for the similarity between parasite eggs and modern versus older eggs were consistent with the second prediction for color; the results for patterns on the eggs were more complex, and varied depending on the element: dispersion, contrast, marking size, and proportion coverage. In terms of the former two, parasites seem to be doing a good job chasing hosts. Pattern dispersion and contrast in current-day parasites better mimic current-day hosts than past hosts, whereas in historical parasites these traits showed poorer mimicry of contemporaneous hosts versus hosts that parasites had not yet encountered. This suggests that for these traits the parasite is evolving quickly, thus improving in mimicry.
Looking at marking size and proportion coverage, hosts seem to have the edge:
By contrast, for marking size and proportion coverage current-day parasites are poorer mimics of current-day hosts than they are of historical hosts, while historical parasites are better mimics of contemporaneous hosts versus hosts that they had not yet encountered. This suggests that with respect to these traits the parasite is evolving more slowly than the host and thus growing poorer in mimicry.
They infer that these different aspects of the egg patterns seem to be evolving independently.
Finally, their third prediction, that more variation in hosts should be observed was borne out by their observations.
In sum, over the course of just a few decades, they find evidence of the battle between host and parasite, with hosts evolving a greater diversity of egg phenotypes, and the parasites chasing them. Because these species are locked into a co-evolutionary race, there’s no reason to think that they will settle into a static equilibrium, so we should expect to see continued changes away from the present phenotypes. Which is cool, since it means more pretty eggs for the foreseeable future.
NorthEastern Evolutionary Psychology Conference
The sixth annual meeting of the NorthEastern Evolutionary Psychology Society starts today. It is hosted by Plymouth State University, and is the annual meeting of the NorthEastern Evolutionary Psychology Society (NEEPS), a regional “sister organization” of the Human Behavior and Evolution Society. This year’s meeting has a number of features that look interesting, including a Feminist Evolutionary Psychology Society Workshop, a 5K (meeting, according to the program, at 5:45 in the morning), and a performance by Canadian rap artist Baba Brinkman. David Zehr is the conference host, and Benjamin Crosier is the program chair. As I write this, the forecast is for temperatures to dip below freezing only briefly on Friday and Saturday nights.
Information is here, and the program is available online.
The 2D:4D Ratio: A New Paper Points the Finger
The 2D:4D digit ratio is the ratio of the length of the second finger to the fourth finger – pointer divided by ring finder – and, it seems to me, new research comes out all the time from researchers looking at the relationship between 2D:4D and something. The reason is that this ratio has been believed to be a record of how much a developing fetus was exposed to androgens during development and therefore masculinized. A new paper, just out online (paywall) in Evolution and Human Behavior adds important new evidence to this research area.
Hampson and Sankar, in a paper entitled, “Re-examining the Manning hypothesis: androgen receptor polymorphism and the 2D:4D digit ratio,” point out that while hundreds of studies have been conducted on this issue, a key finding that emerged at the start of this line of work has not been replicated. In particular, they point to a key paper (also published in Evolution and Human Behavior) by Manning et al. (2003), who measured 2D:4D ratios and also took genetic measurements, specifically looking at repeat polymorphisms in a gene known to be involved with androgen receptors. This relationship was taken to be evidence that relative differences in androgen exposure during early development could lead to small differences in the 2D:4D ratio.
Hampson and Sankar suggest that there is some evidence which seems to be consistent with this finding, but also review a small number of studies that cast some doubt on it. So, they measured 2D:4D ratios of 152 men and genotyped them to look at this relationship. (They also measured ‘bioavailable’ testosterone.)
Quoting from their results section:
Despite a highly typical range and distribution of both 2D:4D ratios and CAG numbers, we found no evidence of a positive correlation between CAGn and either the right 2D:4D ratio, r=−.085, p=.327 [95% confidence interval (CI)=−.251 to .086], or the left 2D:4D ratio, r=−.063, p=.468 (95% CI=−.230 to .108), in our sample.
They also reported that testosterone levels didn’t significantly correlate with the genetic variability.
It’s unlikely that the work is underpowered; their power analysis indicates a greater than 90% chance of finding a significant correlation if the size of the true correlation were comparable to that found in the original paper.
There has been a certain degree of skepticism surrounding this area for some time. In 2004, Putz et al. (yet again in Evolution and Human Behavior) wrote a paper called, “Sex hormones and finger length: What does 2D:4D indicate?”, concluding, more or less, not much. Quoting from their abstract:
In the present study, we reassessed the relationships among three measures of 2D:4D (left hand, right hand, and mean) and several variables previously claimed to be related to 2D:4D, including sexual orientation, spatial ability, status, physical prowess, and components of reproductive success. In addition, we examined the relationship between 2D:4D measures and several other traits whose expression is thought to be related to sex hormones, including voice pitch, sociosexuality, mating success, and fluctuating asymmetry. 2D:4D measures showed highly significant sex differences, as did spatial ability, sociosexuality, components of reproductive and mating success, and fluctuating asymmetry. However, out of 57 correlations, 2D:4D correlated significantly in the predicted direction only with sexual orientation (for both sexes) and only for left hand 2D:4D.
Having said that, the same year Putz et al was published, Lutchmaya et al published some findings from a study in which testosterone and estradiol were recorded from pregnant women in their second trimester of pregnancy in 1996 and 1997. The digit ratios of the children were then measured when they were two years old. The sample was more modest than the Hampson and Sankar study – 33 children – but they found a reasonably strong relationship between the ratio of the two hormones and the digit ratio, accounting for about a quarter of the variance.
So, I don’t know. I should note that I am certainly no expert in this area. From the Putz et al. data, it looks to me that the relationship with sexual orientation is probably really there, and there is presumably some third variable that causes both. Is that third variable androgen exposure in utero? I’d be interested in any experts’ views out there.
References
Hampson, E., & Sankar, J. S. (in press). Re-examining the Manning hypothesis: androgen receptor polymorphismand the 2D:4D digit ratio. Evolution and Human Behavior.
Lutchmaya, S., Baron-Cohen, S.., Raggatt, P., Knickmeyer, R., and Manning, J. T., (2004). 2nd to 4th digit ratios, fetal testosterone and estradiol. Early Human Development, 77, 23-28.
Putz, D. A., Gaulin, S. J. C., Sporter, R. J., & McBurney, D. H. (2004). Sex hormones and finger length: What does 2D:4D indicate? Evolution and Human Behavior, 25, 182–199.