Modern first-world societies are all FAR more like one another than they are like “small-scale” societies.
Culture matters, but rarely in the way you think it does. We have a tendency to hype cultural distinctions (vs differences) that don’t matter — such as whether you grew up eating sushi or hotdogs.
Among the cultural differences that DO matter in behavioral research are what we can broadly lump under the category of economic development.
I pointed you to a great paper by Joseph Henrich the other day that blew open the door to this problem in experimental economics (specifically in behavioral game theory).
Today we’re going to look at another study with Henrich, this time with a huge crew of partners, including some of my favorite researchers in the field.1
From the Abstract:
Researchers from across the social sciences have found consistent deviations from the predictions of the canonical model of self-interest in hundreds of experiments from around the world. This research, however, cannot determine whether the uniformity results from universal patterns of human behavior or from the limited cultural variation available among the university students used in virtually all prior experimental work. To address this, we undertook a cross-cultural study of behavior in ultimatum, public goods, and dictator games in a range of small-scale societies exhibiting a wide variety of economic and cultural conditions. We found, first, that the canonical model – based on self-interest – fails in all of the societies studied. Second, our data reveal substantially more behavioral variability across social groups than has been found in previous research. Third, group-level differences in economic organization and the structure of social interactions explain a substantial portion of the behavioral variation across societies: the higher the degree of market integration and the higher the payoffs to cooperation in everyday life, the greater the level of prosociality expressed in experimental games. Fourth, the available individual-level economic and demographic variables do not consistently explain game behavior, either within or across groups. Fifth, in many cases experimental play appears to reflect the common interactional patterns of everyday life.
This paper is a big one (about 60 pages), so I suggest you grab a large cup of coffee and cuddle up with it.
The games they used were the Ultimatum Game, Public Goods Game, and the Dictator Game.
Here are a few quotes that stood out to me.
Early cross-cultural economic experiments (Cameron 1999; Roth et al. 1991) showed little variation among university students. However, in 1996 a surprising finding broke the consensus: the Machiguenga, slash-and-burn horticulturalists living in the southeastern Peruvian Amazon, behaved much less prosocially than student populations around the world (Henrich 2000).
That’s referring to the paper I showed you the other day by Henrich. The 15 small-scale societies they studied are in the map above.
The variability in ultimatum game behavior across the groups in our study is larger than that previously observed in large-scale, industrialized societies (e.g., Camerer 2003, Ch. 2).
The selfishness-axiom violated across the board:
The selfishness axiom was violated in some way in every so- ciety we studied, across all three experimental games (DG, UG, and PGG). Focusing
More evidence against the selfishness-axiom:
Additional evidence against the selfishness axiom comes from our three dictator games: the results here are more transparent than for the UG because the proposer is simply giving money away, anonymously, with no possibility of rejection. In each of the three groups in which the DG was played, offers deviated from the typical behavior of university students and from the predictions of self-regarding models. Mean offers among the Orma, Hadza, and Tsimane were 31, 20, and 32 percent, respectively, of the stake. These mean Dictator offers were 70, 60, and 86 percent of the corresponding mean UG offers for these groups. Few or none of the subjects in these societies offered zero, whereas the modal offer among university students is typically zero (Camerer 2003).
Finally, the results from all six of our public goods games also conflict with the selfishness axiom, with means ranging from 22% among the Machiguenga to 65% among the Aché – see Table 3. Even the Machiguenga data show 62% of the sample violating the income-maximizing prediction of 0%. Among the other groups, no group had more than 5% of the sample making contributions of zero. To our knowledge, this is never seen in one-shot PGGs among students, where a large percentage of players (usually the mode) give zero.
Does within-group differences in sex, age, wealth matter? Not much.
Sex, wealth, and age do not generally account for any significant portion of the variance in game play.
Connections to real life?
The fact that group-level measures of economic and social structure statistically explain much of the between-group variance in experimental play suggests that there may be a relationship between game behavior and patterns of daily life in these places. In several cases the parallels are striking, and in some cases our subjects readily discerned the similarity and were able to articulate it. The Orma, for example, immediately recognized that the PGG was similar to the harambee, a locally initiated contribution that Orma house- holds make when their community decides to pursue a public good, such as constructing a road or school. They dubbed the experiment “the harambee game” and contributed generously (mean 58% with 25% full contributors).
And among whale-hunting people:
Among the whale hunting peoples on the island of Lamalera (Indonesia), 63% of the proposers in the ultimatum game divided the pie equally, and most of those who did not, offered more than half (the mean offer was 58% of the pie). In real life, when a Lamalera whaling crew returns with a large catch, a designated person meticulously divides the prey into predesignated parts allocated to the harpooner, crew members, and others participating in the hunt, as well as to the sail maker, members of the hunters’ corporate group, and other community members (who make no direct contribution to the hunt). Because the size of the pie in the Lamalera experiments was the equivalent of 10 days’ wages, making an experimental offer in the UG may have seemed similar to dividing a whale.
And on the “negative end”:
While the Hadza ex- tensively share meat (and other foods to a lesser degree), they do not do so without complaint, and many look for opportunities to avoid sharing. Hunters sometimes wait on the outskirts of camp until nightfall so they can sneak meat into their shelter (Marlowe 2004b). The Hadza share because they fear the social consequences that would result from not sharing. Cooperation and sharing are enforced by a fear of punishment that comes in the form of informal social sanctions, gossip, and ostracism (Blurton Jones 1984; 1987). Many Hadza proposers tried to avoid sharing, and several of them were punished by rejection. Thus, we find two foraging peoples, the Aché and the Hadza, at opposite ends of the UG spectrum in both offers and rejections, with each seeming to reflect their differing patterns of everyday life.
These few paragraphs make a good case for Behavioral Game Theory:
Behavioral game theory – the subdiscipline from which our experimental methods derive – is rooted in the notion that individuals will select among alternatives by weighing how well the possible outcomes of each option meet their goals and desires. Theoretically, this is operationalized by assuming that agents maximize a preference function subject to informational and material constraints. Behavioral game theory shows that by varying the constraints and the rewards, as assessed by the agent’s preference function – as we do in such games as the UG and PGG (Charness & Rabin 2002; Fehr & Schmidt 1999) – we can determine the arguments of the agent’s preference function and how the agent trades off among desired rewards. We call this the preferences, beliefs, and constraints approach.
It is often thought that this preferences, beliefs, and constraints approach presumes that individuals are self-regarding, and/or that they have very high levels of reasoning or omniscience. However, though this has often been true of many models, these assumptions are certainly not necessary. Indeed, our research (along with much other work) shows that such considerations as fairness, sympathy, and equity are critical for understanding the preference functions of many humans, and can be effectively integrated with such things as pleasure, security, and fitness to produce a more complete understanding of human behavior. Similarly, these models do not necessarily presume anything in the way of reasoning ability, beyond that required to understand and perform in everyday social contexts.
The relationship between culture-gene coevolutionary theory and the preferences, beliefs, and constraints approach is straightforward, although rarely illuminated. As background, evolutionary game theory has shown that social interactions among populations of individuals with adaptive learning mechanisms often produce multiple stable social equilibria (Fudenberg & Levine 1998; Gintis 2000; Weibull 1995; Young 1998). As different human ancestral groups spread across the globe and adapted their behavioral repertoire to every major habitat from the malarial swamps of New Guinea to the frozen tundra of the
Siberian Arctic, they would have, over time, culturally evolved different social equilibria (forms of social organizations and institutions).15 As a consequence, ancestral humans would have needed to adapt themselves ontogenetically to the vast range of potential social equilibria that one might encounter upon entering the world. The result of dealing with this adaptive problem, we argue, is that humans are endowed with cultural learning capacities that allow us to acquire the beliefs and preferences appropriate for the local social environment; that is, human preferences are programmable and are often internalized, just as are aspects of our culinary and sexual preferences. The preferences become part of the preference function that is maximized in preferences, beliefs, and constraint models. Norms such as “treat strangers equitably” thus become valued goals in themselves, and not simply because they lead to the attainment of other valued goals.
Take the bold line seriously: “… human preferences are programmable…”
Meditate & train every day. Be your own programmer.
As is often the case, the footnotes are as interesting as anything else in the paper. Here are a few that caught my eye.
Some readers may have gotten the impression that economists had not done any cross-cultural work prior to our project from Krupp et al.’s statement that, “Any experimental economist implicitly operating on the premise that American undergraduates are representative of humankind must feel chastened. To some extent, this is déjà vu for psychologists, who have repeatedly seen cross-cultural studies complicate simple views of human nature.” To clarify: The first ultimatum game (Güth et al. 1982) was done in Germany, and the literature jointly emerged from the U.S. and Europe. Within a decade, Roth et al. (1991) had done a good comparative study among students from Pittsburgh, Jerusalem, Ljubljana, and Tokyo showing little variation in offers. Then, and still before our project, a 1996 working paper appeared by Lisa Cameron using students and faculty in Indonesia (Yogyakarata), which also showed little variation in offers from previous studies (Cameron 1999).
And another discussing Neuroeconomics:
Neurobiologists could rightly argue that heuristics do not provide accurate descriptions of psychological processes, but progress in neuroeconomics is closing the gap between abstract reduced-form descriptions and neural detail (e.g., Camerer et al. 2005).
On the difference between empathy and other-regarding preferences:
We are less enthusiastic about the result on empathy discussed by Lucas & Wagner. Empathy should not be conflated with other-regarding preferences, since empathy is possibly an excellent tool for a fully self-interested individual to figure out how to manipulate conspecifics.
Why you must keep up with modern research — it changes!
Heintz cites Axelrod’s (1984) seminal work of two decades ago (see also Axelrod & Hamilton 1981). Substantial research since then – hundreds of papers – have modified and overturned some of Axelrod’s findings (e.g., Bendor 1987; 1993; Bendor et al. 1996; Bendor et al. 1991; for a brief introduction to work since Axelrod, see Henrich & Henrich, in press: Ch. 3). In one instance of this literature, by allowing individuals to develop social networks of cooperative relationships, Hruschka and Henrich relaxed the assumption that individuals’ payoffs are independent of the decisions of individuals they did not play directly and show that “niceness” (cooperate on first interaction) toward other group members is not a general characteristic of successful strategies in pairwise interactions (Hruschka & Henrich, in press). 10.
That last point is essential in all science, certainly so in game theory! Far too often, outside of math and economics, students are taught material that is (at least) 30 to 50 years old.
I’m convinced that the MAJOR reason that the social sciences have failed to embrace game theory (as a whole) is precisely because they have the mistaken belief that “game theory = classical game theory + rational actor model”.
They have no idea what modern research in game theory looks like, or that it even exists. They can hardly be blamed for rejecting what game theorists themselves have rejected!
If these same people were introduced to game theory (from the beginning!) in a more modern way I suspect they would embrace it with excitement, recognizing how valuable the tools would be to their own interest areas.
And from the conclusion:
… the project of understanding the nature of human sociality depends on the integration of theories and methods from across the human sciences. Data must come from the entire range of human societies and social roles within them, as well as from nonhuman primates and other relevant species (e.g., cetaceans). Methods must integrate meticulous field observations with experiments as well as physiological measures. Both evolutionary theory and proximate psychological or behavioral theories need to continue to press towards increasingly rigorous formalizations, which facilitate testing, model comparison, and the assessment of both individual and population level heterogeneity (Davies), while sticking closely to the incoming empirical findings.
Now go lift something heavy,
PS. If you want to learn more about how Game Theory can help us understand human behavior better — and how that applies to sports and coaching — check out the Nemesis Journal
- What? Some people watch sports, I watch science… and a few sports like Weightlifting and Sumo. ↩