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Foundations of Human SocialityEconomic Experiments and Ethnographic Evidence from Fifteen Small-Scale Societies$

Joseph Henrich, Robert Boyd, Samuel Bowles, Colin Camerer, Ernst Fehr, and Herbert Gintis

Print publication date: 2004

Print ISBN-13: 9780199262052

Published to Oxford Scholarship Online: January 2005

DOI: 10.1093/0199262055.001.0001

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The Ultimatum Game, Fairness, and Cooperation among Big Game Hunters

The Ultimatum Game, Fairness, and Cooperation among Big Game Hunters

Chapter:
(p.413) 14 The Ultimatum Game, Fairness, and Cooperation among Big Game Hunters
Source:
Foundations of Human Sociality
Author(s):

Michael S. Alvard

Publisher:
Oxford University Press
DOI:10.1093/0199262055.003.0014

Abstract and Keywords

The Ultimatum Game was played with a group of traditional big game hunters: the Lamalera whalers of Nusa Tenggara, Indonesia, whose community is described in the first section of the chapter. The methods used for the study are then outlined and the results presented and discussed. The results were consistent in some ways with those from trials in western societies, with the primary difference that there were a number of cases of hyper‐fairness: one interpretation offered of these cases is that the whale hunters made strategic decisions when they made fair offers, but other explanations are also examined on the basis of the results of various cross‐cultural studies (including those in this book). These focus on the rejection of both fair and hyper‐fair offers in the Ultimatum Game (which have been interpreted as indicating an unwillingness to punish), and the issue of the variance seen in the cross‐cultural sample in this book in relation to fairness, for which strategic risk reduction is one explanation, but reputation effects are another, and the best model incorporates market integration and payoff to cooperation. The final section of the chapter discusses evolutionary theory and adaptive responses in relation to human cooperative behaviour.

Keywords:   adaptive responses, big game hunters, cooperation, cross‐cultural studies, evolutionary theory, fairness, human cooperative behaviour, indonesia, lamalera whalers, market integration, nusa Tenggara, payoff to cooperation, rejection of offers, reputation, strategic decision making, strategic risk reduction, ultimatum Game

The Field Site

The Ultimatum Game was played with a group of traditional big game hunters, the Lamalera whalers of Nusa Tenggara, Indonesia. The village of Lamalera is located on the island of Lembata, in the province of Nusa Tenggara Timur, in the country of Indonesia. The inhabitants of Lamalera speak Lamaholot, a language ranging in distribution from east Flores to central Lembata. The village is culturally similar to other Lamaholot speakers, sharing a system of patrilineal descent, and asymmetric marriage alliance between descent groups. The village population is approximately 1,200, divided into twenty-one major patrilineal clans (suku), the larger of which are further divided into subclans (lango béla—see Barnes 1996 for detailed ethnography).

Although whaling occurs throughout the year, two separate seasons are recognized. Léfa refers to the primary whaling season from May until October. This is the dry season and the period when sea conditions are best. During léfa, boats go out daily, weather permitting. Baléo refers to the opportunistic pursuit of whales during the balance of the year. It also corresponds to a season of fewer resources. Boats are kept in their sheds, and hunts only occur if prey are spotted from shore. It seems clear that sea conditions increase the costs of search—winds drop in this season and boats must be rowed during search (Barnes 1996: 152). Whether prey are also scarcer is unknown. The primary prey for both seasons are sperm whale (Physeter catadon), and ray (Manta birostris, Mobula kuhlii, and Mo. diabolus). They also pursue other toothed whales, including killer whale (Orcinus orca), pilot whale (Globicephala macrohynchus), several species of dolphin as well as shark, and (p.414) sea turtle. Interestingly, Lamalera hunters taboo baleen whales (suborder Mysticeti). The mean number of whales taken by Lamalera hunters per year during from 1959 through 1995 was 21.4 (SD = 13.8; range 2–56; data from Barnes 1996: table 15). For ray for the same period the mean taken per year was 144.7 (SD = 95.7; range 10–360; Barnes 1996: table 15).

Twelve clans are associated with corporations that own, maintain, and operate whaling operations focused around vessels called téna. These craft measure about 11 meters in length and 2.5 meters at the beam, have thick wood hulls, are propelled by either oars or large rectangular woven palm sails, and are steered with a rudder. Killing prey with a téna is a manifestly cooperative activity, impossible to accomplish alone. The téna alep (téna owner) organizes téna activities. His role is in some ways similar to that of the umialik or whaling captain of the Inuit bowhead whale hunters of north Alaska (Spencer 1959). In spite of the name, the téna alep does not own the téna in a real sense. Rather, he works like a coach or manager, and does not necessarily go out to sea. The téna alep acts as a nexus for the whaling operation as he functions to coordinate three specialized and overlapping interest groups—crew members, corporate members, and technicians who all receive shares of the harvest according to their roles (see below).

Crewmembers tend to be clansmen of the corporation that owns the boat, but this is not a prerequisite. Within crews, the specialized roles are harpooner, harpooner's helper, bailers, helmsman, and crew. Corporate members are usually clan members who underwrite the construction and maintenance of the téna. They may or may not act as crewmembers. The technicians—the carpenter, sail maker, smith, and harpoon bamboo provider (often the harpooner) may or may not be clan members or crew.

Crews of at least nine and up to fourteen or more man the boats. During the whaling season a fleet of boats leaves daily at sunrise (weather permitting) to search an area directly to the south of the coast at a distance of up to 13 km. When a whale is sighted, the sails are dropped and the crew rows furiously to catch up with the whale. Once the boat is in range, the harpooner leaps from the small harpooner's platform on the bow of the boat, to drive the harpoon into the back of the whale. The whale then dives or tows the boat about until it is exhausted. By almost any standard whale hunting is dangerous. Boats can be towed out to sea, and often capsize. (p.415) Barnes (1996: 307–9) describes a litany of woes that have befallen hapless Lamalera whalers. For a good narrative describing a Lamalera whale hunt, see Severin (2000).

The téna travel in a diffuse group and cooperation between boats is common. Large whales (e.g. adult male sperm whales) are difficult animals to catch and more than one téna is often required to subdue one. A mutually agreed upon norm dictates that additional téna will not assist unless the téna that has struck the whale first requests help. Requesting help is made with careful calculation, because each additional téna that participates in the kill has an equivalent claim to the carcass. After help is requested, the helping téna may attempt to place additional harpoons or they may tie on to the first boat. The téna then act as drogues to tire the whale. During the course of a whale pursuit, téna are often swamped or capsized. Téna also assist one another by recovering hunters who have been thrown overboard. Cooperation among téna is not required for smaller prey such as ray.

The type of systematic norm-based sharing of game found at Lamalera is not uncommon among hunting people (Gould 1967; Damas 1972; Robbe 1975; Ichikawa 1983; Altman 1987; Cassell 1988). In the Lamalera case, I define the primary distribution as the distribution of meat to shareholders that occurs during and immediately following the butchering of the prey. Secondary distributions refer to transfers between households subsequent to the primary distribution. The primary distribution proceeds according to complex norms that are generally consistent between corporations, but may vary in detail with prey species. During the primary distribution, the prey is divided into whole shares with names that correspond to anatomical parts of the prey. For example, for a whale, there are fourteen major whole shares that vary in size and quality. Each whole share has one or more shareholders to what I call individual shares. For more detail on the norms of distribution see Alvard (2002) and Barnes (1996).

Whole shares can be described by the nature of the recipients. First, crewmembers receive shares. These shares go to the active hunters that were crewmembers on the téna when the prey was captured. Second, certain corporate members receive corporate shares as part of hereditary rights. Third, shares go to the craftsmen who may or may not be clan members or crew. Fourth, there are shares that go to two clans whose members are descendants of the (p.416) original inhabitants of this part of Lambata Island. These shares are given only from sperm whale and represent concession given in exchange for use of the land. Finally, there are small discretionary shares usually given out by the téna alep.

Within whole share types, division becomes complex. Within a crew, for example, there are five positions: harpooner, harpooner's helper, two bailers, helmsman, and crew—who may receive special shares depending on the species. Bailers, for example, receive the fai mata share from ray. This is a share similar to a standard crew share with portions from the head instead of gill sections. Corporate shares also vary—for a whale there are six corporate whole share types. Some are small in size with many shareholders; others are larger with few shareholders.

Finally, it is important to note that multiple shareholders receive all their shares. That is, being a technician and corporate shareholder does not preclude one from crewing and receiving crew shares as well. For example, a man who is a crewmember, has a corporate share, and is the sailmaker for a téna that kills a whale, receives all three shares.

Besides whaling, there are few alternatives for acquiring meat or other forms of animal protein. Little animal husbandry is practiced. Some goats, chickens, and pigs are kept, but grazing is poor. The common alternative to whaling is the relatively non-cooperative hook-and-line or net fishing with small boats called sapã. Sapã fishing occurs commonly during the baléo season, but also occurs during the léfa season. Some men specialize in sapã fishing year around. Sapã fishing is accomplished alone or in teams of two. While sapã fishing is much less cooperative than whaling and can be accomplished alone, in practice it often involves cooperation among a small number of men. The fishermen often cooperate with sapã and net owners. When this happen, each fishermen and each owner claims a share. Share size is proportional to the number of claimants (Alvard and Nolin 2002). Other less common methods to obtain marine resources include spear gun fishing and fish trapping. Women also gather shellfish and seaweed.

The village of Lamalera is located on the side of a collapsed volcanic caldera, the soil is extremely rocky and steep, and little agricultural land is available. A few villagers have obtained land outside the village (Barnes 1986) or attempt to grow a minimal amount of produce in the rocky ground between houses (p.417) (Barnes 1974). Villagers largely depend on trade to secure agricultural goods. The women of Lamalera trade fish and whale meat, and to a lesser degree salt, lime from coral, and dyed weavings with the agricultural communities of the interior of the island. In exchange they receive maize, other carbohydrates such as rice and cassava, as well as other foodstuffs such as coconuts, coffee, sugar cane, citrus fruits, and green vegetables. Women generally conduct trade on a barter basis without the mediation of cash (Barnes and Barnes 1989). Nonagricultural goods like pots and cloth are obtained in markets located in larger towns on the island. However, few people—such as schoolteachers—have a steady source of cash income. A primary source is from villagers who leave to work for cash elsewhere and send money back to the village. Tourists also provide cash income for some villagers.

Methods

The data were collected in August of 1999. Data were collected with three groups: one group of eleven proposers (mean age = 39.4 years, all male), one group of nine proposers (mean age = 33.4, all male), and one group of twenty responders (mean age = 38.14 years; seventeen males, three females), for a total of forty individuals. Players were explained the rules of the game as groups. The rules were read in Indonesian. All adult Lamalerans are fluent in Indonesian. After all players assured me that they understood the game, numerous sample offers and responses were presented until I was confident that all understood the game. One individual was rejected because he did not understand the game. Each player was presented with a numbered slip of paper. The left half of the slip has a space for the proposer to write his or her offer. The right half of the slip has two checkboxes, marked reject or accept. Proposers were asked to write the number of their offer in the space provided on the slip. The slips were then collected. Players were told to return at a later time to see if their offers were accepted and collect possible winnings.

Responders were given slips with offers indicated on the left side. They were asked to examine the offer, decide to accept or reject, and indicate their choice by checking the appropriate box. After all had indicted their decisions, slips were returned to me and payment was made immediately.

(p.418) The pot consisted of one carton of ten cigarette packs. Proposers were told they could make any offer between 0–10 packs. Cigarettes were used so that people would not associate the activity with gambling. Cigarettes are highly valued by all people. Eighty percent of the players smoked and cigarettes could easily be given or sold to someone for money or favors. Packages of sixteen cigarettes were priced at approximately Rp3,500, and a carton costs about Rp35,000. At the time, the exchange rate was approximately Rp7,400 to one dollar, so the pot was equivalent to $4.73. This amount is equivalent to approximately 10 days wages, although wage labor was generally not available in the village. A schoolteacher who has worked for 5 years in Lamalera earns around Rp200,000 per month. A minibus driver in the island town of Leoleba makes around Rp100,000 per month. I paid our cook/house person Rp90,000 per month. For comparison, the price of 1 liter of rice is approximately Rp2,600 ($0.35), 1 liter of kerosene cost Rp400 ($0.05), 5 liters of cooking oil cost Rp28,000 ($3.78), and one egg cost Rp700 ($0.09); local markets charged Rp2,500 ($0.34) per liter of onions.

After the first round of data collection with the first group of eleven proposers, it was apparent that a range of offers would not be forthcoming. For the first group of eleven proposers, ten offered five packs and one offered eight. In order to examine responses to a range of offers, I created twenty sham offers consisting of four offers each of 1–5 packs. These sham offer slips were presented as genuine to the twenty subjects acting as responders.

Members of the groups involved in any particular trial were able to communicate with one another. It was impossible to prevent players from talking to one another before and after the sessions. After data collection began, the game became a hot topic of conversation, especially among the crews who spend long hours together on uneventful foraging trips. Players were not, however, able to communicate with their partners in the game, who remained anonymous.

Results

The results of the Ultimatum Game with the whalers were consistent in some ways with the results obtained from trials in western (p.419)

The Ultimatum Game, Fairness, and Cooperation among Big Game Hunters

Fig 14.1. Distribution of offers in the Ultimatum Game (n=19, stake size S=10 packs of cigarettes)

societies. Figure 14.1 presents the offers for the sample of nineteen proposers. Like most previously reported trials, the modal offer was 50 percent (twelve out of nineteen). There was one offer of four packs. Compared with standard western results, the primary difference at Lamalera was that there were a number of cases of hyper fairness. Over 31 percent of the offers (six of nineteen) were greater than five packs; the mean offer was 5.8 packs. Hyper-fair offers also occurred in the crosscultural sample with the Ache of Paraguay (Hill and Gurven, Chapter 13, this volume) and the Au and Gnau of Papua New Guinea (Tracer, Chapter 8, this volume). There was a slight effect for age with respect to offers. Youth was associated with greater offers. Individuals that made offers over 50 percent were more likely to be in their twenties (R 2 = 0.20, p = 0.05, F = 4.25, df = 17).

Responses were consistent with previous results in the sense that the rate of rejections increased as the size of offers decreased (Figure 14.2). Twenty-five percent of offers consisting of three packs or less were rejected. The mean rejected offer was two packs. In spite of the tendency for low offers to be rejected, many low offers were, in fact, accepted—75 percent of three packs offers or less were accepted. Men who were wealthy by Lamaleran standards made two of the four rejections. One is a schoolteacher who, in (p.420)

The Ultimatum Game, Fairness, and Cooperation among Big Game Hunters

Fig 14.2. Rejection rates as a function of offer size in the Ultimatum Game (n=20) (stake size S=10 packs of cigarettes)

addition to having a salary, runs a home-stay for tourists who visit the village. The other was an ex-village head. He worked most of the year for cash in Leoleba, the largest town on the island, and was reported by some to be ‘the wealthiest man in the village’ (this anecdotal finding parallels that of Ensminger, this volume). The other two rejecters were our neighbors. They may have been more concerned about reputation than others. In fact, one neighbor made sure to tell me that he had rejected the offer and that he did so because he considered the offer of two packs to be unfair. In the same breadth, however, he lamented the loss of the two packs of cigarettes, which he would have dearly enjoyed smoking. It is also possible that our neighbors may have valued the cigarettes less than others since they regularly obtained smokes from us via inter-household demand sharing (Peterson 1993). The players who accepted low offers were téna crewmembers with little opportunity to obtain cash or other forms of wealth.

Discussion

One easy interpretation suggests that the Lamalera whale hunters made strategic decisions when they made ‘fair’ offers (Forsyth et al. (p.421) 1994; Hoffman, McCabe, and Smith 1996a, b). In this case, when proposers offer fair amounts, they are acting to mitigate the risk that responders will reject the offer. If this hypothesis is true, the whalers' ‘fair’ proposals are not anomalous from either an economic or evolutionary point of view because fair offers are predicted from an assumption of self-interest. Bodega owners cooperate with the mafia—because if they do not, their legs may be broken. This makes intuitive sense when we think about the success of the mafia and other coercion-based organizations that use intimidation and threat of reprisal as powerful methods to induce cooperation. In this interpretation, the proposer ‘cares’ about the responder's welfare to the extent that their two interests are linked. In the Ultimatum Game, the proposer's fate is linked to the responder's. If the proposer cannot induce the responder to cooperate and accept the offer, the proposer receives nothing.

Data from Dictator Games support the idea that offers in the Ultimatum Game are high in order to avoid rejection. In the Dictator Game (see Camerer and Fehr, Chapter 3, this volume for details), proposers have no expectations about the behavior of responders. Since there is no risk of rejection, very low offers are expected. Experiments show that offers are significantly lower when the risk of punishment is removed (Forsyth et al. 1994; Hoffman et al. 1994; Hoffman, McCabe, and Smith 1996a). It seems that proposers ‘care’ less about the responder when their fates are not linked. Support for the strategic hypothesis also includes the work reviewed by Roth (1995) that showed that offers are often optimal in the sense that they maximize the payoff given the probability of rejections. Using the crosscultural data set, analysis by Henrich et al. (this volume), however, does not point to the same conclusion. In all but two cases, the mean offer was higher than predicted given the probability of rejection. In the Lamalera case, given the observed range of rejections, the expected income-maximizing offer is predicted to have been around 31 percent of the pot (Henrich et al., Chapter 2, this volume). It seems clear that in the Lamalera case, the mean of 58 percent cannot result from risk aversion.

The fact that Henrich et al. (Chapter 2, this volume) shows that most of the mean offers in the crosscultural sample were greater than the income-maximizing optimal, given the distribution of rejections, suggests there may be more to the issue than strategic offers. Additional evidence comes from the Dictator Game. While (p.422) offers in the Dictator Game are lower than offers in the Ultimatum Game, they are still not what is predicted by selfish rationality. Even when rejection was not an option, a nontrivial proportion of players give substantial portions of the pot away (Hoffman et al. 1994; Hoffman, McCabe, and Smith 1996a). Results with the three Dictator Game played in the crosscultural sample also indicated that many people gave shares away (Henrich et al., this volume).

Hoffman, McCabe, and Smith (1996a) created a number of additional treatments to the Dictator Game designed to increase the degree of ‘social distance’ between players and experimenters. Offers were substantially lower when the experimental design was such that complete anonymity was assured to the proposers. In these trials, nobody, including the experimenter, knew the offer. Only 11 percent of the subjects gave 30 percent or more to their partner. Hoffman increased assurance of social anonymity in these cases, and ‘fair’; behavior essentially evaporated. Similar results were obtained when the experiment was repeated—64 percent of offers were $0 (Hoffman, McCabe, and Smith 1996a).

Hoffman et al. (1994) suggest that players are not only strategically motivated to avoid rejection, but also play as if they are concerned about what others think of them. This implies that in the standard Ultimatum Game, some players make their offers as if there may be future interactions, in spite of the fact that the game is designed in a way to get subjects to exclude these possibilities. A number of other researchers have also hypothesized that at least some portion of the results are due to players behaving as if their reputations are at stake (Baird, Gertner, and Picker 1994; Eckel and Wilson 1998, 1999; Tullberg 1999). This may be particularly true in games played with non-western, traditional peoples who have little experience with experimental methods.

These results suggest that the subjects and the experimenters that run the games are playing by different rules (Kollock 1998). Experimenters simplify the real world, create the rules of a game, and have faith that their subjects play by them. Players may view the experiment in a different way—as a game within a game (Burnell, Evans, and Yao 1999). That is, one possible hypothesis to explain ‘fairer’ than optimal offers is that players make decisions as if the game is part of a larger game where reputation is important—the larger game does not end with the experiment (Hoffman, McCabe, and Smith 1996a). The whale hunters and others who make fair (p.423) offers may do so because they are considering how their decision will have impacts beyond the scope of the game.

The best evidence from the crosscultural sample is Tracer's (Chapter 8, this volume) work with the Au and Gnau of New Guinea. These people rejected both fair and hyper-fair offers in the Ultimatum Game. Tracer interprets this to be the result of a pattern of politics through gift giving common in these societies. Among these groups accepting gifts obligates one to reciprocate—a situation that people work hard to avoid. As Henrich et al. (Chapter 2, this volume) point out: ‘With this knowledge, the New Guinea result makes perfect sense.’ I agree with this interpretation, but it is true only if either the Au and Gnau have a sense that their play is not anonymous, or believe the anonymity but bring non-selfish preferences into the game that they acquired from daily life outside the game (in other words, in the context of the game, the anonymity of the player does cause them to ignore their non-selfish preferences: see Henrich et al., Chapter 2, this volume and Ensminger, Chapter 12, this volume). If the Au and Gnau players ‘believed’ the games were anonymous and they have only selfish preferences, they should have harbored no fear that they would be obligated, and they should have accepted fair offers. On the contrary, it appears that they rejected offers because they did not want to risk having to reciprocate.

Of course, while anonymity may have affected behavior in certain cases, it remains difficult to explain why groups like the Hadza, Tsimane, Machiguenga, and Quichua, who live in places in which anonymity is nearly non-existent, made such low offers. Further, along these lines, both Henrich and Smith (Chapter 5, this volume) and Hill and Gurven (Chapter 13, this volume) compare treatments in which player decisions were publicly known to standard anonymous versions of the games and find no difference.

What About Those Rejections?

Rejections in the Ultimatum Game have been interpreted to indicate a willingness to punish, at a cost, those who are unfair in economic relations (Bolton and Zwick 1995). Above, I noted that some researchers believe that ‘fair’ offers may be due to players acting as if the game is a subgame of a larger game where reputation (p.424) is important. Responders' spiteful punishment observed in the Ultimatum Game might also be part of a general phenomenon related, at least in part, to signaling a willingness to punish noncooperators. Indeed, in addition to assortative interactions among cooperators, punishment of noncooperators has also been suggested to be critical for the development of cooperative outcomes (Boyd and Richerson 1992; Clutton-Brock and Parker 1995; Bowles and Gintis 1998). From this perspective, responders who reject low offers are concerned with their reputations—of course, this still leaves us with the puzzle of why individuals in about half the groups in our sample were unwilling to reject, or only rejected very low offers with low probability.

There are theoretical reasons as well as recent empirical research by evolutionary ecologists to support this idea. Many nonhuman organisms make costly displays to signal their qualities to others. Costly signaling theory suggests that advertising costly traits indicates phenotypic quality because only individuals of such quality can exhibit maximal expression of these traits. Also called the handicap principle (Viega 1993; Zahavi 1997), the most notable example is mating displays like those found in peacocks. Male peacocks have enormous feather displays that are used to attract females to mate. The display is costly because it attracts predators, takes resources to maintain, and restricts mobility. According to the handicap principle, the males that can maintain such displays are signally their quality as mates.

Costly displays have been suggested to work in a similar way in humans. Smith and Bird (2000) argue that a wide variety of seemingly inexplicable and maladaptive behavior in humans may be understood in terms of costly signally theory. Smith and Bird cite such behaviors as genital mutilation and foot binding (Mackie 1996), monumental architecture (Neiman 1998), and expensive public rituals like the potlatch among the Kwakiutl (Boone 1992). For such behaviors to be stable signals, they must be observable, costly, reliable in the sense that they must vary with the quality of the trait being communicated, and of course, they must ultimately provide some benefit to the sender.

What might low-offer rejection in the Ultimatum Game signal? One possibility is that they signal an unwillingness to cooperate with noncooperators. If a low offer represents a defector move, accepting such an offer is essentially cooperation in the face of (p.425) defection. In games of reciprocity, in which some have argued that the Ultimatum Game is actually embedded, cooperating with a defector is essentially a sucker move, and returns a lower payoff than any defect move. If people behave as if these games are not anonymous, rejecting low offers communicates the fact that they are not dupes. While costly in the short term, such a reputation could be critical in economies where cooperation is vital yet where a perception by others of weakness could be exploited and result in loss.

Subjects in Lamalera are quite willing to punish others for norm transgressions. Here is an example. Bob was the téna alep or boat leader for Ibu Téna, one of the whaling vessels. At a party, Fred became drunk and punched Bob's daughter in the head. The reason was unclear. Fred is the harpooner for Ibu Téna. For a period of weeks, Bob would not allow Fred to harpoon from Ibu Téna. This punishment acted to ground Ibu Téna, because a téna cannot go to sea without a harpooner and no other harpooner was willing to replace Fred. Harpooning is a very specialized skill that few men possess. Not only was Fred punished, but so were the crew and corporate members of Ibu Téna, as well as Bob himself. They failed to obtain any resource that might have been harvested if Ibu Téna had not been grounded. What is even more interesting is that since harpooners are in short supply, Fred was able to harpoon for another boat and did not suffer.

Another example comes from Barnes (1996: 79) who anecdotally describes what might be described as a cheater clan named Lefo Sefo that existed in Lamalera until the turn of the nineteenth century. Their téna, the Fao Puka, was very successful but would only allow clan members as its crew. They also would not return their harvest to the normal beach spot where all other téna butchered and distributed prey. They would butcher at a spot called Lodo Ika. Subsequently, they were punished when other boats did not offer assistance after the Fao Puka capsized during a hunt, and as a result many of her crew drowned. The clan was ostracized afterwards and the last clan member died in the 1920s.

Fairness and Big Game Hunting

I have not yet addressed any of the variance seen in the crosscultural sample. Yes, perhaps strategic risk reduction explains fair offers—when offers are fair. And, perhaps reputation effects explain costly (p.426) rejections—when rejections occur. But as the various chapters in this volume attest, not all people play fair and not all low offers are rejected. The whale hunters represent only one extreme in terms of play in the Ultimatum Game. What explains the variance? One hypothesis is that players play fair in the game to the extent that cooperation is an essential aspect of their economic lives (see Hoffmann, McCabe, and Smith 1996a: 654; Henrich et al. Chapter 2, this volume). If the payoffs to cooperation are high in day-to-day economic life, cooperative payoffs will be valued, norms of cooperation will be strong, reputation as a cooperator, and punisher will be important, and people will be disposed to play fair in the Ultimatum Game. If payoffs to cooperation are low, as Henrich argues is the case for the Machiguenga (this volume), a lack of fairness will be expressed in the game.

This hypothesis is supported by the crosscultural data (Henrich et al. Chapter 2, this volume). We rank-ordered the fifteen societies according to their degree of market integration, privacy, anonymity, and payoffs to cooperation. We regressed mean Ultimatum Game offers on these variables and found that the best model incorporates market integration and payoff to cooperation. I will discuss the market integration parameter below and focus for the moment on the role of cooperation. The Lamalera whale hunters are in a unique position. Lamalera represents the extreme within the crosscultural sample with respect to payoffs to cooperation in the peoples' daily lives. They also had the highest mean offer in the Ultimatum Game.

Humans are by far the most cooperative of the primates as well as the most variable. In many societies, people engage in cooperative tasks that either provide greater per capita returns when accomplished in groups, or simply cannot be accomplished alone. I have argued elsewhere that in many cases of cooperation, individuals have immediate common interest and cheating does not pay. Such joint activity is not readily modeled by the Prisoner's Dilemma payoff schedule, and is best described as mutualism or coordination (Alvard 2001; Alvard and Nolin 2002; see Camerer and Fehr, Chapter 3, this volume, for a discussion of the Prisoner's Dilemma and coordination games).1

(p.427) In contrast to the payoff schedule of a Prisoner's Dilemma, in a coordination game, cooperating with a cooperator is better than cheating with a cooperator. These games are sometimes called ‘trust games’ or assurance games (Sugden 1986; Binmore 1994). Coordination games can be structured in the same way as a Prisoner's Dilemma, but with a different payoff matrix. In a Prisoners Dilemma it pays to cheat no matter what a partner does; in a coordination game it pays to cooperate when partners cooperate.

The Lamalera whalers are a perfect example. Unless eight men can coordinate to crew the boat, no one goes to sea. In Lamalera, the mean return for cooperative whale hunting is significantly higher than solitary fishing 0.66 kg/h versus 0.37 kg/h (for details see Alvard and Nolin 2002). In the whaling coordination game, choosing to whale is the best choice, unless your partners choose to fish and you are left whaling alone with a zero payoff. In other words, to the extent that individuals receive benefits from cooperation, we expect them to cooperate—provided they have assurance of their partner's behavior. In Lamalera, there is also a complex division of labor and task specialization that provides economies of scale. For payoffs to be realized, however, significant coordination problems must be solved (Becker and Murphy 1992). Sailmakers, for example, must trust that crews will form and go to sea. Oarsmen must be assured that harpooners will attempt to kill prey. If multiple téna are involved in a kill, distribution norms must be coordinated or different boats could lay claim to the same shares. Such coordination is not always as easy as one may intuitively think. Experimental evidence shows that even in coordination games where there is one pareto-dominant Nash equilibrium, players do not always converge (van Huyck, Battalio, and Bei 1990).2 How the coordination is obtained in Lamalera is unknown, although there are some suggestions (Alvard and Nolin 2002).

(p.428) Among many big game hunters, Lamalera included, distribution and pursuit norms seem designed to assure participants of how others will behave and the payoffs they themselves will receive. The entire system does seem premised on the implicit assumption by participants that all will receive the payoff prescribed by the norm of entitlements. Ellickson (1991) argues that norms function to reduce transaction costs for achieving cooperative outcomes. Transaction costs are the costs of establishing and maintaining property rights and include such activities as inspection, enforcing, policing, and measurement (Allen 1991). Imagine the transaction costs for determining claims to téna harvests if norms of distribution did not exist for the whalers at Lamalera. For the whale that was killed on 11 June 1999, three téna participated and at least ninety-nine individuals were due and received shares according to the norms of the primary distribution (Alvard and Nolin 2002). It seems unlikely that these individuals would have participated in such an activity if transaction costs could not be minimized and payoffs assured.

Mutualistic subsistence strategies similar to that found in Lamalera may be a particularly strong environment favoring the type of fair-minded cooperation displayed by the Lamalerans and others in the Ultimatum Game. The larger set of rules that guides players' behavior during the Ultimatum Game is certainly generalized from norms based on real-world socio-sexual economic exchanges. One working hypothesis is that general learning about fairness (i.e. equity) is common in societies where the payoffs to cooperation are greater. In societies where folks commonly develop norms to solve coordination problems, fairness becomes a focal point (Schelling 1960) because the cooperatively obtained payoff must be divided (e.g. fair meat distributions). This is not a common problem in more solitary and less cooperative systems like the Machiguenga. To the extent that achieving such fairness is critical for subsistence, we expect fairness to be expressed in the Ultimatum Game. In the Ultimatum Game, players must coordinate in the sense that the proposer must make an offer that the responder will accept—if anyone is to get a payoff. In some societies fairness may be a focal point that helps proposers coordinate with responders.3

(p.429) Coordination may be a key for understanding the fairness that dominates Ultimatum Game results in western societies. Western society is arguably more cooperative than any of the groups in the crosscultural sample discussed in this volume. In societies like the United States, where specialists are critical to the economy, the cooperation that results is mutualistic. Assuming that the results in the Ultimatum Game game reflect culturally inculcated norms of fairness, the high degree of mutualistic cooperation found in western societies may explain the Ultimatum Game results found in those groups. This hypothesis is supported by the result obtained when we regressed mean Ultimatum Game offers on market integration. Market activity involves complex norms of fairness. The payoffs of exchange cannot occur unless fair agreements can be reached between players (Moulin 1995). One interpretation is that people who do not have experience with markets do not play the Ultimatum Game as if they are infused with such norms of fairness (Ensminger, Chapter 12, this volume; Henrich and Smith, Chapter 5, this volume).

Conclusion

Evolutionary theory assumes that natural selection plays the critical role in the evolution of adaptive responses, especially for behaviors that have a strong bearing on reproductive outcomes, such as mating, parenting, and socioeconomic decisions like those modeled by the Ultimatum Game (Smith 1992a, b; Smith and Winterhalder 1992; Rose and Lauder 1997). Since neoclassical economics and many evolutionary approaches to behavior share the common assumption of rational selfishness, it is not surprising that researchers who use evolutionary theory to understand behavior share the sense of incongruity with the Ultimatum Game's initial (p.430) results with western study populations. But as evolutionary theory was preparing to explain the incongruous result of a seemingly human universal preference for fairness, the target moved. As the results in this volume show, people do not universally play fair. The question is no longer why do people seem to have a preference for fairness. The question is now: do people behave more or less fairly in adaptive ways?

Recent approaches that use evolutionary theory for understanding human cooperative behavior have focused on trying to discern the mechanisms important in the development of Homo sapiens' understanding of risk and reward in a social context. In other words, knowing the social economics of our ancestors is a key for understanding the results in the Ultimatum Game in living populations. These cognitive and behavioral tools likely evolved during the so-called Environment of Evolutionary Adaptedness (Tooby and Cosmides 1992; Foley 1995). What might the conditions have been in our evolutionary past that patterned the expression of fair or unfair exchange?

If current forager and nonhuman primate models are accurate (e.g. Tooby and DeVore 1987), it seems clear that we evolved in an environment where strangers were rare. A good argument can be made that in our evolutionary past, few economic exchanges were anonymous. This is surely the case among contemporary foragers (e.g. Aspenlin 1970; Bahuchet 1990; Kent 1993; Peterson 1993; Caulfield 1994; Hill and Hurtado 1996). Foraging communities, while fluid, consist of small groups of people who are generally known by all members. Even in Lamalera, with a population of 1,200, the number of men who ever hunted was just over 300—a group where all could easily be acquainted. The social environment was one where most, if not all, economic interactions occurred between non-strangers and relatives, and where reputation was important.

If this is true, there are no good reasons to expect humans to be particularly adapted (in an evolutionarily sense) to anonymous exchanges (but see Fehr and Henrich 2003, for counter argument). There is much to suggest that we have a preference to try to avoid them. Hoffman et al. (1994) discuses the anonymity that comes with the ‘Great City’. It is cooperation in spite of the supposed anonymity of modern economic exchange that has motivated much research in the field of economics (Bowles 1998). While anonymous exchanges between individuals have become more common with the (p.431) rise of complex society, people rely on symbols to make the exchanges less anonymous. I do not know the clerk behind the counter at McDonald's, but I know ‘McDonald's’. In this sense, the exchange is not anonymous. Such a trademark is a symbol that is very costly to imitate, and identifies and distinguishes the source of the goods or services of one party from those of others (PTO 1989). Trademarks in western economics, like clan totems, language, costumes, scarification, tattoos, rituals, and other identifiers indicate association with groups and decrease anonymity (see Barth 1969).

One hypothesis that has limited support is that outcomes in Ultimatum Game vary across societies with the payoffs to cooperation in the day-to-day life of the members of those societies. In societies where cooperation is commonly mutualistic, individual actors ‘need’ others to achieve the maximum payoff, fairness norms are common, and reputation as a cooperator is preferred. ‘Concern’ for the fitness of others displayed when the Ultimatum Game is played with such groups occurs because mutualistic cooperation is so essential to life that it translates to the game. Since such norms are costly, it makes sense that norms of fairness vary in adaptive ways depending on the payoffs to cooperation. In some societies, like the Machiguenga, cooperation is not nearly as integral a part of subsistence…and Machiguenga play the Ultimatum Game very differently than do the whale hunters and members of western society.

Having allies can often be critical to survival—cooperation often does pay compared with defection, especially in economic systems like that of the whale hunters. Greater-than-zero offers, even in a context where punishment is unlikely, as is the case with the Dictator Game, may indicate that some people are willing to pay in order to maintain reputations as cooperators. They play as if there exists the threat of punishment even though the game rules disallow it. In other words, humans may prefer not to have a reputation of being a cheater among those whose cooperation is valued. Conversely, in contexts where cooperation does not pay relative to solitary pursuits, players may not be willing to pay the costs associated with maintaining a reputation as a cooperator.

Understanding how cooperation works under realistic conditions is the key next step for understanding the variance seen in the results of the Ultimatum Game game. Indeed, in retrospect, given (p.432) the costs involved in maintaining and enforcing norms, it makes evolutionary sense that such norms not be fixed but rather vary in adaptive ways. Whether or not this is the case remains to be seen.

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Notes:

(1) It should be noted that there are two types of mutualism—a point not often appreciated in the literature (Alvard 2001). According to Brown (1983), by-product mutualism involves behaviors that ego must accomplish regardless of whether others are present or not. Whale hunting, however, is not something a hunter can accomplish unless he is in a group. A second kind of mutualistic cooperation is called synergistic mutualism by Maynard-Smith and Szathmary (1995). The difference between synergistic mutualism and by-product mutualism lies with the returns obtained from going it alone. In this case, the payoffs of hunting large game alone are lower than small game alone and hunters must coordinate to receive the greater payoff. This is not the case for by-product mutualism.

(2) A Nash equilibrium is a game theoretical concept that describes a combination of players' strategies that are best against one another. At a Nash equilibrium, no players will do better by changing their decision unilaterally. A pareto optimum, in contrast, is the outcome in which no player can do better except at the expense of the other players.

(3) What does fairness mean to a group like the Ache, where meat-sharing norms dictate sharing such that good hunters subsidize poor hunters (see Kaplan and Hill 1985a)? It may mean that the currency with which fairness is judged varies. Fairness exists when players receive shares from a cooperative venture proportional to the costs they have paid. Benefits and costs are often not paid in the same currency—much to the chagrin of the field anthropologist. Good hunters among the Ache are reported to be disproportionally named as partners in extra-marital affairs (Kaplan and Hill 1985b). Warriors who kill among the Yanomamo have more wives and father more children (Chagnon 1988). One can imagine that fairness in such contexts becomes difficult for even the actors themselves to measure (see discussion of Ellickson (1991) above). The fact that ‘keeping track’ is so difficult may be one of the reasons why norms arise: by acting as easy-to-maintain rules of thumb.