NETWORK CENTRALITY AND COALITIONAL COMPETITION: AN ECONOMIC EXPERIMENT IN AN ACHUAR AND SÁPARA COMMUNITY OF THE ECUADORIAN AMAZON ______
A Thesis
Presented to the
Faculty of
California State University, Fullerton ______
In Partial Fulfillment
of the Requirements for the Degree
Master of Arts
in
Anthropology ______
By
James G. Zerbe
Thesis Committee Approval:
John Q. Patton, Division of Anthropology, Chair Elizabeth Pillsworth, Division of Anthropology Brenda Bowser, Division of Anthropology
Spring, 2017
ABSTRACT
One instance of a cooperation dilemma consequential to humans is inter- coalitional competition and conflict. Here, results are reported from a series of five one- shot anonymous public goods games (PGG) designed to elicit varying coalitional and competition motivations for cooperation within the PGG. The data presented in this thesis were collected in Conambo, a bi-ethnic tribal community of Achuar and Sápara peoples in the Ecuadorian Amazon. This research has two aims: (a) discern the relative influence of group composition, random or coalitional, and the level of group competition, either none, intra-group, or inter-group on cooperation; and (b) test predictions concerning how variation in social network centrality affects cooperation in intergroup competition.
Analyses of experimental PGG treatments reveal a significant increase in offers due to variation in group composition (from random to coalitional) in the context of between- group competition. Additionally, betweenness centrality in an alliance network was found to differentially affect cooperative offers in men and women across a range of coalitional and competitive contexts. These results give further confidence that group competition is a robust factor increasing cooperation and limited support for the argument that inter- individual differences rather than group level differences explain variation in PGG offers.
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TABLE OF CONTENTS
ABSTRACT ...... ii
LIST OF TABLES ...... v
LIST OF FIGURES ...... vi
ACKNOWLEDGMENTS ...... vii
Chapter 1. INTRODUCTION ...... 1
2. THEORETICAL BACKGROUND ...... 4
The Problem of Cooperation...... 4 Evolutionary Game Theory ...... 5 Indirect Fitness Mechanisms ...... 7 Direct Fitness Mechanisms ...... 9 Coalitional Aggression and Human Evolution ...... 16 The Human-Chimpanzee Connection ...... 17 The Archaeology of Prehistoric Violence ...... 20 The Ongoing Debate ...... 22 Mechanisms of Coalitional Aggression ...... 31 Inter-Individual Differences and Collective-Action ...... 37 Evidence from Economic Experiments ...... 38 Individual Variation in Social Capital ...... 42 Social Network Analysis ...... 43 Summary ...... 48
3. ETHNOGRAPHIC CONTEXT ...... 49
Introduction, Location, and Ecology ...... 49 Social Organization and Demography ...... 50 Subsistence Patterns ...... 52 Recent History of Violence in Conambo and Surrounding Areas ...... 53 Achuar and Sápara Ethno-histories...... 55 Achuar History ...... 56 Sápara History ...... 58 Summary ...... 61
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4. METHODS AND HYPOTHESES ...... 62
Information-Sharing Network Task ...... 62 Successive Pile-Sort: Coalitional-Alliance Network ...... 64 Public Goods Game ...... 66 Hypotheses ...... 70 Coalitional Effects on Cooperation ...... 70 Competition Effects on Cooperation ...... 71 Social Network Centrality Effects on Cooperation ...... 72
5. ANALYSIS AND RESULTS ...... 74
Information-Sharing Network Analysis...... 74 Coalitional-Alliance Structure ...... 75 Hypothesis Testing ...... 79 Cooperation in Coalitional and Competitive Contexts ...... 80 Network Centrality and Cooperation ...... 89
6. DISCUSSION AND CONCLUSION ...... 94
Discussion ...... 94 Cooperation in Coalitional and Competitive Contexts ...... 94 Cooperation and Centrality ...... 97 Conclusion ...... 105
APPENDICES ...... 109
A. PUBLIC GOODS GAME ENGLISH PROTOCOL ...... 109 B. PUBLIC GOODS GAME SPANISH PROTOCOL ...... 112
REFERENCES ...... 115
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LIST OF TABLES
Table Page
1. Coalitional and Competitive Conditions of the PGG ...... 70
2. Descriptive Statistics of Information-Sharing Network Centrality Variables ..... 85
3. Descriptive Statistics of Alliance Strength ...... 77
4. Descriptive Statistics of Alliance-Network Centrality Variables ...... 79
5. Descriptive Statistics of PGG Offers ...... 81
6. Mixed ANOVA Omnibus Test of PGG Offers...... 81
7. Mixed ANOVA Omnibus Test of PGG Round Order ...... 83
8. Mixed ANOVA Contrast of Treatment One and Three ...... 84
9. Mixed ANOVA Contrast of Treatment Two and Four ...... 87
10. Mixed ANOVA Contrast of Treatment One and Two ...... 87
11. Mixed ANOVA Contrast of Treatment Three, Four, and Five...... 88
12. Mixed ANOVA Contrast of Treatment Four and Five ...... 89
13. Hierarchical Regression of PGG Offers and Information-Network Centrality ... 91
14. Hierarchical Regression of PGG Offers and Men’s-Alliance Network Centrality ...... 92
15. Hierarchical Regression of PGG Offers and Women’s Alliance-Network Centrality ...... 93
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LIST OF FIGURES
Figure Page
1. Prisoner’s dilemma payoff matrix ...... 6
2. Typical distribution of Achuar and Sápara households in Conambo ...... 50
3. Map of the regional ethnosphere...... 57
4. Information-sharing network by coalition and sex ...... 75
5. Multi-dimensional scaling of men’s alliance strength ...... 76
6. Multi-dimensional scaling of women’s alliance strength ...... 77
7. Men’s alliance-network diagram ...... 78
8. Women’s alliance-network diagram ...... 78
9. Bar graph of average offers across PGG treatments ...... 82
10. Bar graph of average offers in PGG treatments one and three by coalition ...... 85
11. Bar graph of average offers in PGG treatments one and three by sex ...... 86
12. Women’s alliance-network: node size scaled by betweenness scores ...... 100
13. Scatterplot of women’s betweenness centrality and treatment four offers by coalition ...... 101
14. Men’s alliance-network: node size scaled by betweenness scores ...... 102
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ACKNOWLEDGMENTS
I want to acknowledge the support and encouragement I have received from my mother and father: Charla and Maylon Zerbe. Everyone has their path through life and
I’m grateful that they have always trusted me to know and pursue my own path to the best of my ability. For their continuing support through my recent studies and the whole of my life I dedicate this thesis to them.
Every data point presented in this thesis was collected in the community of
Conambo, Ecuador and depended upon the combined efforts of many different parties.
First, I want to graciously thank the people of Conambo for sharing their way of life with me and their willing participation in this research. There are three people who deserve special recognition for their supportive efforts in the data collection process. Dr. John
Patton deserves my enduring gratitude for his mentorship, patience, and support at every stage of development of this thesis. The least of which is sharing his seemingly boundless knowledge, enthusiasm, and improvisational prowess in the most austere of field working conditions. He embodies the spirit of adaptability; I am proud to call him my friend. For her generous involvement in this research I extend sincere thanks to Damaris Santi, the best field worker and team mate an anthropologist could ask for. Without her linguistic capabilities in seamlessly switching between Spanish, Achuar, and Quichua and her familiarity with seemingly every person in Conambo this research surely would not have be accomplished. Additionally, Mateo Peñaherrera Aguirre provided a key element in the
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successful collection of this data. His insight and efforts vastly improved the methodology and coordination of the public goods game so vital to this thesis. I met him serendipitously and his involvement in this project transpired seemingly on a whim and I look forward to more fruitful collaborations with him in the future.
For their support, I want to extend my immense appreciation to the rest of my thesis committee: Dr. Elizabeth Pillsworth and Dr. Brenda Bowser. I couldn’t ask for more hardworking, knowledgeable, and professional individuals to emulate. They provided numerous comments, suggestions, and motivation that enhanced this thesis.
Additionally, the ANTH 504 proposal writing course lead by Dr. John Bock deserves recognition. He is a valuable source of empowerment to students and their ambitious research proposals. I thank him for his concerted effort which greatly influenced this thesis.
Recognition also goes to my cohort. They include Amanda Barnes-Kennedy,
Megan Fox, Jennifer Gruendling, Holly Pittaway, and Jeremy Pollack. Their comradery and solidarity were much appreciated elements of my time at CSUF and I received insightful comments and encouragement from all of them.
I also acknowledge the financial support I received to conduct this research from the CSUF division of Anthropology. The funds provided by the Wallenberg peace award and the Sadovszky international research award were critical aspects of coordinating this project and I am honored to have received them.
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CHAPTER 1
INTRODUCTION
An open question in the evolutionary approach to studying human behavior is how to adaptively account for human cooperation. Cooperative tendencies are considered difficult to explain given the fitness-vulnerability of cooperators when interacting with defectors. These interactions result in defectors accruing individual reproductive benefits to the detriment of cooperators. Given these reproductive payoffs to both actors, cooperation should not spread in a population of defectors, or be able to resist the introduction of the free-riding strategy into a population of cooperators. However, many animal species as well as all human societies exhibit impressive and varied patterns of cooperation between individuals.
Coalitional conflict and warfare is an instance of this cooperation dilemma and a collective-action problem. In other words, a context where multiple individuals would all be better off paying a cost to achieve a shared benefit that cannot be realized by acting alone, but contribution to the group benefit is individually costly, which incentivizes rational and self-regarding individuals to free-ride (Olson, 1965). Coalitional violence and tribal warfare is one such example in human societies (Glowacki & Wrangham,
2013; Mathew & Boyd, 2011, 2014; Patton, 2000), and is widely theorized to have been an important factor in the evolution of human social behavior, moral sentiments, and political and societal complexity (Alexander, 1979, 1987; Bowles, 2009; Flinn, Geary, & 2
Ward, 2005; Strate, 1982; Turchin, 2010). Coalitional aggression is potentially costly, due to injury and mortality risk, but if successful the potential benefits include gained territory, resources, mates, security and deterrence, which are, to a great extent, collectively consumed and non-excludable (Glowacki & Wrangham, 2015; Mathew &
Boyd, 2011, 2014). This confluence of individual costs in producing collective benefits presents individuals with the incentive to free-ride. Given this cost-benefit structure and the incentive to free-ride, how can evolutionary theory account for coalitional aggression?
Here I test predictions from a recently developed computational model of collective-action that incorporates heterogeneity in the costs and benefits of cooperating and between-group competition. Gavrilets and Fortunato (2014) explicitly model the concurrence of in-group variation in social rank and between-group competition as a possible mechanism to solve the cooperation dilemma. They argue that higher ranking individuals are incentivized to contribute the effort necessary to maintain the public-good
(i.e., to succeed in between-group competition), because they have a greater ability to benefit from success than lower ranking individuals and if unsuccessful to experience greater costs, or that they have a greater endowment than others of some relevant resource, making their contribution less costly. Due to these varying cost-benefit structures across individuals, high-ranking individuals can afford higher costs of contribution since they have lower relative costs associated with contributing and greater relative costs with not contributing to the public good (Gavrilets & Fortunato, 2014).
This research investigates the key attribute of an individual’s social network centrality as a relevant domain of individual variation that can influence the relative costs
3 and benefits of cooperating coalitionally against competitors. Specifically, a series of economic experiments are performed that approximate the same incentive structure as the collective action dilemma inherent in coalition competition and analyses are performed to test how network centrality influences cooperation. Additionally, varying experimental treatments are designed to elicit coalitional and competition motivations into game structure: the relative influence of group composition, either random or coalitional, and the level of competition at which conflict occurs, either none, intra-group, or inter-group, are examined for influencing contributions in group cooperation. Participants include indigenous Achuar and Sápara people of Conambo, Ecuador; a small-scale Amazonian community of coalitionally divided hunter-horticulturalists.
The following chapter provides a theoretical overview to more fully expand on the topics of: the problem of cooperation, coalitional aggression and human evolution, inter-individual differences in collective-action, social network analysis, and experimental economic games that invoke social dilemmas. Subsequently, chapter three presents the ethnographic context of this research with attention toward establishing the appropriateness of this case study with regards to research concerning coalitional competition. Chapter four summarizes the hypotheses tested in this thesis and the methods used, which include social network analysis and the details of the public goods games (PGG) played in Conambo. Chapter five presents the data analyses and the results of the tested predictions. In chapter six these results are discussed in relation to the relevant literature and final conclusive remarks are made.
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CHAPTER 2
THEORETICAL BACKGROUND
The Problem of Cooperation
The focus of this thesis is the problem of cooperation. Understanding cooperation is critical since basic evolutionary theory is seemingly at odds with social behaviors that are concurrently costly to perform and benefit the evolutionary interests of other individuals (Darwin, 1859; Hamilton, 1964a). Such instances of cooperation abound in nature; risky predator inspection occurs in a number of fish species, some bird species use alarm calls to alert conspecifics to the presence of predators, blood-sharing meals occur between vampire bats, grooming behaviors are common among non-human primate species, and policing among honeybees has been observed (Dugatkin, 1997).
Further emphasizing the importance of cooperation is its relevance to the evolution of biological complexity and the hierarchical levels of organization that permeates life; cooperation is inherent in the origins of compartmentalized genomes, eukaryotic life, zygotes and sexual reproduction, multicellular organisms, societies, and interspecific mutualisms (Bourke, 2011; Smith & Szathmary, 1997). This section will survey the theoretical and empirical literature on the evolutionary biology of cooperation and will theoretically frame the mechanism of cooperation tested by this thesis. Specifically, it is argued that the cooperation dilemma is critical in understanding the human behaviors involved in coalitional conflict and the mechanisms that favor cooperation in coalitional
5 conflicts are surveyed. To these ends an exposition of evolutionary game theory is first presented.
Evolutionary Game Theory
Evolutionary game theory provides a valuable set of tools in the modeling of strategic social interactions among rational actors (Smith, 1982). There are three necessary elements for any game: players, strategies, and payoffs. Players simply represent the individuals involved in a given social interaction. Strategies represent different behavioral phenotypes an individual can deploy in the interaction with the strategies of other players to produce particular payoffs. Payoffs are understood to be some proxy currency relevant to biological fitness that is awarded to each player contingent on the outcome of the game. Strategies with higher payoffs (i.e., reproductive success), then reproduce in greater frequencies in accordance with their payoffs as compared to less fit strategies with lower payoffs. This is how certain behavioral strategies increase or decrease in frequency in a population over iterative rounds of interaction, or biological generations.
Game theory has been critical in the development of theory and research on the evolution of cooperation (Axelrod, 1984). A game known as the prisoner’s dilemma is often utilized in researching the biological and logical constraints of cooperation, given its ability to model the fundamental conflict inherent to social life, that is, the conflict between individual and collective interests (McElreath & Boyd, 2008). The payoff matrix for a prisoner’s dilemma game clearly defines the expected costs and benefits to two players given any possible combination of the strategies of cooperation and defection (see
Figure 1).
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Figure 1. Prisoner’s dilemma payoff matrix. Reprinted from The Evolution of Cooperation (p. 8), by R. M. Axelrod, (1984), New York: Basic Books.
The prisoner’s dilemma is formally defined as a game with the following payoff structure: T > R > P > S. Where T represents the temptation of defecting on a cooperating partner; the most individually beneficial and selfish result since the defector doesn’t pay a cost but still benefits from their partner doing so. R denotes the reward outcome where both players cooperate and achieve the greatest collective payoff. When both players defect, they are said to produce the P or punishment outcome, referring to their inability to generate any outcomes from mutually beneficial cooperation. The S outcome is the inverse scenario experienced by the cooperator who is defected on and is termed the sucker’s payoff. Given these outcomes, universal defection is expected since no other strategy by another player can increase their payoff unilaterally when interacting with a defector (Colman, 1999). This is called the Nash equilibrium, which is the individually maximizing strategy in the interaction with any possible strategy of the other player
(Nash, 1950). While the combination of strategies that maximize group benefit (both players cooperating) is termed the Pareto optimum. Where it is impossible for a player to change their strategy away from the Pareto optimum strategy and increase their payoff without making the other player worse off (Buchanan, 1962). In the prisoner’s dilemma
7 defection is the Nash-equilibrium, or evolutionary stable strategy; a behavior, that when dominant in a group, cannot be invaded by an alternative behavioral strategy (Smith &
Price, 1973). Therefore, the prisoner’s dilemma adequately captures and exhibits the key features in the conundrum of the evolution of cooperation.
However, the term “problem of cooperation” is somewhat of a misnomer.
Cognitive scientist Steven Pinker (2003) succinctly encapsulates the relevance and interest in cooperation when he states,
the megalomania of the genes does not mean that benevolence and cooperation
cannot evolve, any more than the law of gravity proves that flight cannot evolve.
It means only that benevolence, like flight, is a special state of affairs in need of
an explanation, not something that just happens (p. 53).
Research on cooperation in both ethology and the study of human behavior has largely been concerned with testing how well these various mechanisms explain behavior in an array of cooperative contexts. Two general sets of theoretical explanations have developed to account for cooperation. One set includes those explanations that posit direct fitness benefits for performing cooperative acts, while the other includes explanations of indirect fitness consequences (fitness comprised of the effects on aiding the reproduction of related individuals) favoring the evolution of cooperation (West,
Griffin, & Gardner, 2007).
Indirect Fitness Mechanisms
Kin-selection. A critical development in theory of the evolution of cooperation was formulated by Hamilton (1964a) with his argument on the evolution of helping behavior among kin, known as kin-selection or inclusive fitness. Hamilton (1964a)
8 argued that even though natural selection should result in selfish individuals accruing greater fitness, limited altruistic behaviors can be explained if they confer a fitness advantage on kin, that is, those individuals who share alleles through descent. Therefore, genes can advance their own evolutionary interests by “altruistically” supporting copies of themselves that exist in other individuals (i.e., genetic relatives). It is the combination of this process of indirect fitness and more traditional direct fitness effects that is given the term inclusive fitness (Hamilton, 1964a). Grafen (1985) gives a slightly modified expression of “Hamilton’s rule” as: rb – c > 0. Where helping behavior can evolve if the benefit to the recipient (b) discounted by their proportion of relatedness to the helper (r) minus the cost to the helper (c) is greater than zero. Kin-selection was originally identified as conferring evolutionary benefits to maximizers of inclusive fitness via the two principles of kin discrimination, and population viscosity (Hamilton, 1964b). Kin- discrimination involves the specific targeting of altruistic acts towards more-related kin and away from less-related or non-kin, while the limited dispersion of kin (population viscosity) leads to the indiscriminate direction of altruistic acts to neighbors, who are overwhelmingly related (Hamilton, 1964b).
The most well-known cases of kin selected altruism exist among many species of social insects (Hamilton, 1964b). Numerous insect species (e.g., specific species of termites, beetles, aphids, ants, bees, and wasps) exhibit high degrees of average relatedness between individuals in a community (Bourke, 2011), and this offers a simple explanation of how natural selection can produce whole classes of individuals who are sterile and work for the reproductive ends of another individual, like an ant queen. In humans, kin have been observed as providing important support in contexts of conflict
9 and combat (Alvard, 2009; Chagnon & Bugos, 1979), allo-parenting (Hawkes, 2003;
Kramer, 2005), and labor exchange relationships (Hames, 1987).
Direct Fitness Mechanisms
Explanations of direct fitness benefits argue that cooperative acts can result in individual fitness benefits that outweigh the costs of performing them. Within this class of direct fitness explanations another distinction is defined by whether cooperative acts to some degree can be enforced or not. Enforced explanations involve mechanisms that preferentially reward cooperators or punish non-cooperators, shifting the cost-benefit structure so that cooperation is individually more beneficial and defection more detrimental. Mechanisms which involve the enforcement of fitness consequences include reciprocal altruism, indirect reciprocity, and strong reciprocity (West et al., 2007).
Reciprocal altruism. The theory of reciprocal altruism posits that dyadic cooperation can be a fitness enhancing strategy if actors interact in a contingent manner, so that the present cost to an actor to help the recipient is less than the benefit to the actor discounted by the probability of be reciprocated by the recipient in the future: wb > c
(Trivers, 1971). In a series of repeated interactions actors are incentivized to cooperate because they have accrued benefits from cooperation with particular individuals previously. Conversely, if an actor has been defected upon by a particular individual then they should defect in return. This allows an actor to avoid accruing further losses or to inflict a cost on the non-cooperating partner and make it clear that future cooperation is conditional. This strategy is widely known as tit-for-tat, and is famous for being a robust and successful strategy when pitted against competing strategies in a computer tournament simulating an iterated prisoner’s dilemma (Axelrod, 1980a, 1980b).
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Evidence exists that humans have mental adaptations for perceiving adherence to or violations of dyadic conditional exchanges in social domains, constituting a psychological adaptation for cheater detection in social contracts (Cosmides & Tooby,
1992). This mechanism is not a product of a general-purpose reasoning ability—as evidenced in the Wason selection task by the differential ability of participants in detecting violations of conditional statements in social contracts but failing to do so in abstract domains. Furthermore, the universality of this particular modular cognitive adaptation is supported by experimental data from cross-cultural research with indigenous peoples. The Wason selection task was replicated among the Shiwiar hunter- horticulturalists of the Ecuadorian Amazon. Like the original American undergraduate participants, the Shiwiar were adeptly aware of logical violations involving social contracts but not in abstract conditions (Sugiyama, Tooby, & Cosmides, 2002).
Additionally, it is theorized that the cognitive infrastructure adapted for dyadic exchanges were possibly elaborated upon by natural selection to imbue humans with cognitive adaptations for engaging in n-person cooperative contexts, like coalitions (Tooby,
Cosmides, & Price, 2006).
Indirect reciprocity. Like reciprocal altruism, indirect reciprocity is a mechanism of enforced cooperation, where decisions to cooperate or defect are free and conditional on whether ego can expect to benefit from mutual cooperation or experience costs from defection with another actor. However, indirect reciprocity does not rely upon acquiring a history of relevant past actions through first hand interactions but rather collecting relevant cues of cooperative intent, via known prosocial reputations of other actors
(Alexander, 1987; Nowak, 2006). Cooperation can evolve via indirect reciprocity if q, the
11 probability of knowing an individual’s reputation, is greater than the cost-benefit ratio of behaving altruistically, that is, c/b. In summary, if q > c/b then cooperation is viable via indirect reciprocity (Nowak, 2006).
Multiple lines of evidence now support indirect reciprocity’s role in enhancing cooperation. Experimental research with a PGG and an indirect reciprocity game reported that only in contexts where participants were able to give or receive direct contributions from others (the indirect reciprocity game) were they likely to behave cooperatively in a
PGG. Other research indicates that reputational dynamics motivate otherwise selfish actors in contributing individually costly effort to group aims (Milinski, Semmann, &
Krambeck, 2002a). Likewise, individuals who were financially charitable to a well- known relief organization (whose beneficiaries are underprivileged non-group members) received greater donations from other group members and had a greater probability of being elected to represent their group’s interests, that is, they enhanced their political reputation (Milinski, Semmann, & Krambeck, 2002b). In addition, an ethnographic study of cooperative labor-exchange relationships in the Caribbean found that men who had the greatest prosocial reputations attracted larger work groups and that this engendered greater choice among whom the high-quality altruist established partnerships with
(Macfarlan, Remiker, & Quinlan, 2012).
Several complex behaviors and traits that typify humans appear critically involved in processes of indirect reciprocity. The greatest of which would be the evolution and use of language to acquire and disseminate information regarding behaviors relevant to prosocial reputations. As such, indirect reciprocity is theorized as an important
12 component of the evolution of human intelligence and moral systems (Alexander, 1987;
Nowak & Sigmund, 2005).
Strong reciprocity. Strong reciprocity refers to humans’ prosocial disposition in cooperating, performing altruistic acts that lower their lifetime fitness while increasing the lifetime fitness of others, and punishing those who fail to do likewise, even at a cost to themselves (Fehr, Fischbacher, & Gächter, 2002; Gintis, 2000; Gintis, Bowles, Boyd,
& Fehr, 2003).
Proponents hold that strong reciprocity is evidenced where individuals (strong reciprocators) from a range of small-scale societies act altruistically toward others in anonymous, one-shot experimental games, with no possibility of being reciprocated in the future or accruing a prosocial reputation (Henrich et al., 2005). This is supported by additional experimental research in cross-cultural and laboratory contexts where second and third-parties are willing to pay costs to inflict costly punishment on selfish players in the dictatorship game (Fehr & Fischbacher, 2004; Henrich et al., 2006). Consistent with general economic theory, strong reciprocity theorists hold that individuals are rational and maximizing decision makers—but they rework a second major assumption of economic theory, that humans maximize self-interested utility. Where the utility function of the individual is maximized if inequity among others is minimized (Fehr & Schmidt,
1999). It is posited that dispositions that favor the costly rewarding of cooperators and punishing of defectors evolved due to the operation of natural selection on these traits at the group level (Fehr et al., 2002). Specifically, the process of cultural rather than biological selection is posited to explain the proliferation of strong reciprocity in humans.
Cultural group selection holds that groups vary in their prosocial norms, that these norms
13 have an effect on group survival or success, and that when individuals move between groups they accept and embody the norms of their new group (Henrich, 2004).
An interesting and pertinent question is how likely are analogous scenarios in human evolutionary history and are humans adapted for one-shot encounters? While it has been argued that one-shot encounters have been under appreciated and can be shown to have occurred in the ethnographic record (Fehr & Henrich, 2003), it is not clear that these initial interaction between strangers where not facilitative of long term relationships and iterative interactions between individuals (Hagen & Hammerstein, 2006). Even if it were so, it is difficult to answer why individuals would be altruistic to anonymous individuals when cultural group selection arguments are predicated upon conditional cooperation towards in-group members (unlikely to be anonymous) and in certain contexts where competition with other cultural groups is an important factor influencing selection (Henrich, 2004). Additionally, it cannot be ruled out that when individuals are placed in these game scenarios cognitive adaptations for reciprocal altruism, which posits that cooperation is a beneficial first move if iterative interactions follow, or reputation management, are active in animating generous and seemingly altruistic offers. Since individuals playing the game are anonymously playing with group members, and they often deduce as much, then assuming that these other cognitive adaptations for cooperation are not operating cannot be done with confidence (Hagen & Hammerstein,
2006). Likewise, the cultural context is important to game behavior (Henrich et al.,
2004). The Au and the Gnau horticulturalists of New Guinea frequently reject hyper- generous offers in the ultimatum game (Tracer, 2004). In this cultural context accepting large gifts places the gifted individual in lower social standing relative to the giver, and to
14 avoid these outcome individuals reject large offers which results in both players receiving a payoff of zero. However, if such cultural contexts do impact game play then it is contradictory to consider game behavior unaffected by other implicit or explicit contexts not defined in the game protocol and that this data supports an altruistic disposition in cooperating with strangers in one-shot interactions (Hagen & Hammerstein, 2006; Smith,
2005). Players cannot simultaneously be affected by the cultural and socioecological patterns of cooperation in their day to day lives and also rationally accept and believe the game conditions that the interaction is anonymous and one-shot. Despite several reservations, strong reciprocity is a critical and recent development in that it is seeks to explain cooperation at a larger scale without relying upon kinship, repeated interactions or known reputations. However, as I’ve discussed above and like every explanation of cooperation described so far, the debate and research concerning how well these theories of cooperation explain empirical facts is active and continuing.
There is another broad theoretical class of mechanisms of cooperation that fall under the heading of non-enforced mechanisms. Non-enforced mechanisms, as opposed to enforced mechanisms, are relevant when individual self-interest is mutualistic and cooperative behavior and collective action is mutually beneficial for the actors involved
(West et al., 2007). One general context is identified in group foraging or hunting, where larger groups are more successful and as a by-product individuals coordinating their actions accrue greater per-capita returns than if they pursued an alternative solitary foraging strategy, such is the case with Indonesian whale hunting boat crews (Alvard &
Nolin, 2002), and packs of lions (Packer & Ruttan, 1988). Many mutualistic contexts are noted for not neatly conforming to the payoffs of a prisoner’s dilemma, instead collective
15 action for mutual benefit has been argued to more closely resemble a coordination game, the “stag hunt” being one such example (Alvard & Nolin, 2002). Another example of by- product cooperation occurs in species that are classified as cooperative breeders.
Cooperative breeding entails individuals besides biological parents paying investment costs in the raising of others’ offspring. In contexts where being a member of a larger group confers greater individual fitness benefits than being in a small group, an individual can increase their fitness by directly augmenting the size of the group by allo- parenting for non-kin to increase group size (Kokko, Johnstone, & Clutton-Brock, 2001).
An important context of cooperation in regards to the evolution of social behaviors in humans is between-group competition and conflict. Individual effort expended in service of this cooperation simultaneously helps other individuals in the group, and by default helps the contributing individual given their membership within this same group. Some researchers consider situations where an individual’s reproductive success in lessened in relation to other group members “weak altruism” (Wilson, 1977).
Though, others note that regardless of whether there are relative fitness differences between group members a “weak altruist” can still accrue individual benefits via their inherent benefit as member of the same group, like the argument for cooperative breeding via group augmentation presented above (West et al., 2007). This distinction has been specifically articulated by defining “whole-group traits” that benefit every member of the relevant group including the actor from “other-only traits” that benefit only group members that are not the actor (Pepper, 2000). It is theorized that individuals will contribute to the public good in contexts of between-group competition and that individual benefit for doing so is greater than the benefit accrued from not behaving
16 cooperatively even though other group members could possibly defect (Gavrilets, 2015;
Gavrilets & Fortunato, 2014). Cooperation in such a context can be further incentivized by differences among individuals of a population in certain domains which imbue individuals with different cost-benefit tradeoffs in expending prosocial effort in these contexts (Gavrilets, 2015; Gavrilets & Fortunato, 2014). This is the focal theory examined by this thesis and is more thoroughly reviewed below in an independent section once other foundational premises to this research are explicated.
This thesis is interested in understanding one form of collective-action and cooperation in humans, namely cooperative behaviors in the context of coalitional aggression, generally defined as when two or more individuals jointly direct aggression or compete against one or more targets (Harcourt & De Waal, 1992). In the following pages, coalitional aggression is referred to by many terms, including: inter-group or between-group conflict, violence, aggression, competition, tribal warfare, coalitionary or coalitional killing, competition, violence etc. These terms or ones used similarly below all refer to the same phenomena.
Coalitional Aggression and Human Evolution
Human coalitional violence and tribal warfare is an example of n-person cooperation (Glowacki & Wrangham, 2013; Mathew & Boyd, 2011, 2014; Patton, 2000) and is theorized to have been an important factor in the evolution of human social behavior and moral sentiments (Alexander, 1979, 1987; Bowles, 2009; Flinn et al., 2005;
Strate, 1982). Coalitional aggression has associated individual costs, primarily injury and mortality risk, while its benefits include gained territory, resources, mates, security, and defense which are collectively received (Glowacki & Wrangham, 2015; Mathew & Boyd,
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2011, 2014). These benefits are of such a nature that individual exclusion from them is impractical, which presents individuals with the incentive to free-ride on the costs to produce them, absent norms of punishment (Ostrom, 1990). Which is the case among politically non-centralized societies that inhabited the social environments in which the cognitive and behavioral adaptions associated with coalitional conflict evolved, and human evolution more generally (Tooby & Cosmides, 2010). Given this incentive to free- ride, effort expended in coalitional aggression constitutes cooperation (Patton, 2000).
The Human-Chimpanzee Connection
Behaviors of collective aggression are proposed to predate the emergence of the genus Homo and be evidenced archaeologically throughout a deep-timeline of human history. First, there are established parallels between hunter-gatherer and chimpanzee inter-group aggression (Wrangham & Glowacki, 2012; Wrangham & Peterson, 1996;
Wrangham, Wilson, & Muller, 2006). Chimpanzees and humans have both been observed to engage in lethal coalitional raiding, which constitutes the most common form of coalitional aggression (Keeley, 1997; Wrangham & Peterson, 1996). Additionally, both species do so under certain conditions: when a state of inter-group hostility exists with surrounding groups and when numerical superiority ensures that an imbalance-of- power between the attackers and the victim(s) makes aggression less risky for the aggressors (Manson et al., 1991; Wrangham, 1999). Coalitional attacks or killings have been observed in the longest-term wild chimpanzee research sites in which chimp communities are non-isolated from other chimp communities nearby: Gombe, Mahale,
Kibale, Budongo, and Taï (Boesch et al., 2008; Goodall, 1986; Mitani, Watts, & Amsler,
2010; Nishida, 1990; Reynolds, 2005). This corpus of reports largely supports aspects of
18 the “model”—that victims are attacked when vulnerable by a numerically superior force, that aggressors experience little risk in attacking vulnerable individuals, only receiving slight scratches in some instances (Watts, Muller, Amsler, Mbabazi, & Mitani, 2006), and that success in aggressing against other communities results in benefits going to the aggressors’ community (Mitani et al., 2010; Nishida, Hiraiwa‐Hasegawa, Hasegawa, &
Takahata, 1985), further supporting that coalitional violence is a beneficial strategy among chimps when successful (Wrangham & Glowacki, 2012). Coalitional aggression is the norm across wild chimpanzee communities, Boesch and colleagues (2007) posit that chimpanzees are aggressive to outsiders across their natural range and types of habitat regardless of the presence of human observation and provisioning, or their level of habituation. Also, in order to control for possible confounding causal influence on chimpanzee inter-group aggression a multisite review of 152 killings support the notion that killing among chimpanzees are adaptive strategies influenced by coalitional context
(Wilson et al., 2014). Specifically, higher population densities were a factor, males were found more likely to be the attackers and victims, and most killings were targeted towards outgroup males when attackers possessed a numerical advantage. Variation in human impacts across the sites had no causal effect on patterns of killings. Additionally, experimental studies with captive chimpanzee populations indicate that male chimpanzees are more likely to confront and react aggressively to stimuli of an out-group adult male when in a larger group of conspecific males (Wilson, Hauser, Wrangham
2001).
Likewise, key parallels in coalitional aggression have been noted between chimpanzee and nomadic hunter-gatherers. Hunting and gathering bands are thought to
19 typify the kinds of societies that all humans belonged to for roughly 95% of human history and are considered important in understanding the context in which modern behaviors and human universals have evolved (Hill et al., 2011; Marlowe, 2005; Tooby
& Cosmides, 1990). As such, many scholars have commented on the frequency, intensity, and importance of hunter-gatherer warfare and violence (Allen & Jones, 2014; Bowles,
2009; Burch Jr, 2007; Ferguson, 2013a; Fry & Söderberg, 2013a; Keeley, 1997; Kelly,
2000; Pinker, 2011). Glowacki and Wrangham (2012) specifically aimed to distill the evolutionary relevancy of these commonalities by analyzing hunter-gather societies that are nomadic, have other nomadic hunter-gatherers as neighbors, are non-equestrian, and that don’t have considerable social relationships with farmers. Their survey of ethnographic sources revealed that like chimpanzees, nomadic hunter-gatherers regularly engage in coalitional raiding when a numerical or strategic asymmetry makes the cost of doing so less risky for themselves and inflict as much harm as quickly as possible before retreating, with aggressors rarely being wounded or killed. An interesting distinction is found in the varying intensity of internal warfare (conflict between coalitions of the same ethno-linguistic group) among humans but not chimps, but that practices of killing trespassers on sight, overt fear of strangers, underused border territories between ethno- linguistic groups or communities, and beneficial group outcomes for successful aggression is shared. Also in unison with data from chimpanzee communities a comparison with twelve hunter-gatherer societies revealed similar median death rates from inter-group conflict (Wrangham et al., 2006).
These similarities support the notion that these behaviors, or at least their precursors, related to coalitional aggression represents a homology in both Homo and
20
Pan, likely present at the time of their last common ancestor 5–6 mya. Though there are details that are different between chimpanzee and human violence that reveal important distinctions. Macfarlan and colleagues (2014) conducted a reanalysis of Yanomamo data and produced support that human alliance-formation in service of coalitional killing is more flexible and extends beyond the constraints of kinship and male philopatry that characterize chimpanzee coalitions in lethal raiding. Also, with humans it’s often the case that reinforcing cycles of revenge raids, representing a runaway social process, are more deadly than the original offense that started the cycle of revenge (Walker & Bailey,
2013). And consequently revenge-seeking has been identified as a distinguishing motivation for aggression amongst hunter-gatherer societies in contrast to chimpanzee raiding (Boehm 2011).
Archaeology of Prehistoric Violence
The scholarship regarding the archaeological evidence of coalitional aggression is highly contentious for a number of reasons. It is difficult to archaeologically discern interpersonal lethal aggression from coalitional inter-group violence. Namely, it is difficult to establish the social identities of the aggressor and the victim, as well as the number of perpetrators involved in any given act of aggression. Both details are important components to many definitions of warfare, which vary among researchers, and lead to varying conclusions given the working definition of warfare that is adopted.
The implications of this are covered more fully below.
Interpersonal violence is easily recognized by perimortem wounds of considerable magnitude on skeletal remains and has been found at numerous sites deep in the evolutionary past (Keeley, 1997). An exemplary case of hominin interpersonal violence
21 from the archaeological record is dated to 430 kya and includes the deadly blunt force trauma wounds exhibited by cranium 17 from Sima de los Huesos (Sala et al., 2015).
Other evidence of considerable antiquity includes cut-marks on hominin skeletal remains, possibly indicating cannibalism (Fernández-Jalvo, Cáceres, & Rosell, 1999). Though, this doesn’t constitute clear evidence of coalitional aggression or killing (Ferguson, 2013b).
While interpersonal violence is clearly discernable there is significant disagreement over specific cases of possible intergroup violence in the archaeological record. One case includes the Predmosti and Dolni Vestonice sites of Paleolithic Europe
(25,000–20,000 BP) which are claimed to exhibit every line of evidence that lead to a conclusion of warfare. Specifically, evidence of a large multifamily dwelling structure, a wall or fence constructed of mammoth bones surrounding the encampment, a settlement location on high ground for defensive purposes, and contemporaneous mass burials of fighting-age men who exhibit head wounds is argued to support the presence of prehistoric warfare (LeBlanc & Register, 2003). Though, others argue that these evidences are misinterpreted or illusory and that the basis for declaring the sites as exhibits of prehistoric warfare is slim (Ferguson, 2006).
There are currently two, nearly universally accepted, instances of coalitional killing that predate the Holocene; the Jebel Sahaba site of Sudan and the Naturuk site of west Turkana. At Jebel Sahaba, a mortuary site discovered in northern Sudan, nearly 40% of recovered individuals exhibited evidence of violent death (Wendorf, 1968). These deaths predate the Holocene (14–12 kya) and are a clear instance of consequential coalitional aggression among hunter-gatherer groups. The recently discovered site at
Naturuk constitutes additional evidence of hunter-gather warfare at the precipice of the
22
Holocene. In this context, of the 12 individuals for which well-articulated skeletal remains were recovered at the edge of a shallow lagoon (12–9 kya), ten exhibited clear signs of violent death. Additionally, these remains show no evidence of deliberate burial and where likely found in the positions in which they originally fell after being attacked
(Lahr et al., 2016).
The Ongoing Debate
This confluence of archaeological evidence of inter-group conflict and homological evidence between nomadic foraging societies and chimpanzee communities strongly supports that coalitional aggression was a critical component in human evolution. However, there are points of evidence taken to be contrary to this general conclusion and a sizable opposition considers human evolution to not have been effected by warfare (Ferguson, 1989a, 2006; Fry, 2006, 2007). I will generally argue that this position is not as well supported as proponents posit and that human evolution and coalitional aggression are linked.
I will specifically focus on a recent article by Fry and Söderberg (2013a) which compares rates of lethal violence among mobile foraging band societies (MFBS) for two reasons: (a) it is heavily cited, it’s recent, and Fry is a well-known scholar who to an extent exemplifies the short chronology of warfare position; and (b) it exemplifies many of the misunderstandings and confusions relevant to this topic. A critique of this piece of scholarship serves to identify and analyze many topics relevant to this broad discussion.
To begin, Fry and Söderberg’s article asks and answers a question not highly relevant to understanding the evolution and nature of coalitional aggression. They seek to quantify the relative frequency of different types of lethal aggression in MFBS, with a
23 focus on discerning whether interpersonal or coalitional aggression was more prevalent
(Fry & Söderberg, 2013a). They claim that since they derived interpersonal killings as more common from their sample, with their definition of warfare, that the coalitionary model is not supported. However, if examined it’s apparent that Fry and Söderberg do not fully comprehend what the model they argue against posits. Evolutionary arguments for the importance of warfare don’t rely upon coalitional aggression being the most common form of aggression, only that coalitional aggression resulted in a mortality rate high enough to influence the evolution of social behaviors (Bowles, 2009). Also, while the overall rates of killing are interesting it is more illuminating to understand how war mortality might disproportionately affect individuals of a certain sex and age class. For example, when Lambert (2002) concludes from her extensive archaeological review of evidence of hunter-gatherer warfare in North America that,
most of the archaeological and osteological evidence suggests that relatively
small-scale engagements predominated, involving a limited number of aggressors
and resulting in relatively few victims per encounter. Quantitative analysis of
victim frequencies reveals, however, that even this low-level warfare could result
in very high death tolls overall, particularly for certain sex and age classes
(p. 229).
Likewise, the pervasiveness of warfare, which is not concretely defined, isn’t a necessary component to the importance of warfare in human evolution. As Bowles
(2013) notes in his reply to Fry and Söderberg (2013a) that what is important is whether mortality rates where great enough to be an important selection pressure. With this point addressed certain statements commonly made in regards to the evolution of war are
24 therefore understood as red-herrings in regards to this question. Such as statements about whether peace was more prevalent than war or whether most lethal violence was interpersonal rather than inter-coalitional.
Another distinct issue concerns how warfare is defined. The relevant aspects of intergroup aggression from the perspective of evolutionary biology include the number of perpetrators involved and the group membership of the aggressors and the victim
(Bowles, 2013). One posed definition of coalitional aggression is when two or more individuals jointly direct aggression or compete against one or more targets (de Waal &
Harcourt, 1992), and when this is slightly modified to include differential group membership of the attackers and victim(s) then it properly encompasses the fundamental features of the phenomena of inter-group aggression or warfare (Bowles, 2013).
Specifically, two actors are the minimum number required to create a social context describable as a cooperation dilemma. Such as the prisoner’s dilemma where one member of a coalition could potentially defect on an alliance partner, or those individuals in an enduring cooperative relationship in coalitional activities (de Waal & Harcourt,
1992). This potential dilemma constitutes the most critical and interesting aspect of coalitional aggression as a behavioral phenomenon. LeBlanc (2014) offers a very similar definition of warfare as socially sanctioned lethal conflict between independent polities, indeed he notes that other definitions often deployed that exclude raiding and ambush behaviors, and conflict within an ethnolinguistic group (categorized rather as feuding and not war) would inherently exclude hunter gatherers a priori without proper justification.
The critical point being a definition of warfare needs be constructed that allows for the
25 possibility of forager warfare, then whether or not the evidence supports that warfare has a long or short chronology can be explored.
A curious feature of Fry and Söderberg’s classification of instances of lethal aggression as either interpersonal or as war are the motives of the aggressor(s). This separates killings motivated by revenge for prior killings, sexual jealousy, or other interpersonal motives from killings spurred by general intergroup hostility, and even though these personal motives animate events of two or more individuals killing a third of another group it is argued that this doesn’t constitute coalitional war (Fry & Söderberg,
2013a). Additionally, Fry (2007) states that,
disputes that at first seemed to be between bands in fact turned out to be personal
grievances between individuals who happened to be living in different bands.
Sometimes such grievances led to revenge against particular individuals or their
close kin, thus constituting personal self-redress, which if reciprocated amounted
to feuding, not war between communities (p. 116).
This separating of lethal aggression among a continuum of reasons from interpersonal to communal is irrelevant to evolutionary theory (Bowles, 2013), even though Fry and
Söderberg (2013a) couch their argument in the parlance of evolutionary theory. Also, the social substitutability of the targets of violence is discounted by this statement, which is often identified as a salient aspect of warfare and coalitional aggression (Kelly, 2000), but it is clear that Fry doesn’t consider other kin members to be substitute targets even though they aren’t the individuals directly involved in some prior personal grievance.
Despite the issues regarding the relevance of their data, research question, and their definition of warfare, it can also be argued that a bias in their sampling procedure
26 influenced their results. Two points of consideration include what kinds of societies were the neighbors of ancestral foraging groups and whether ancestral foraging groups can be represented by modern day MFBS in marginal environments. First, their sample included
MFBS but they didn’t exclude societies with non-MFBS neighbors, which would have not been an evolutionary social context (Wrangham & Glowacki, 2012). They say as much when they posit that “indications of warfare would be rare, especially in regions consisting solely of prehistoric MFBS.” (Fry & Söderberg, 2013b, p. 8). However, as emphatically noted by Gat, Australia provides “a pure, uncontaminated laboratory of hunter-gatherer communities on a continental scale” (Gat, 2015, p. 116), though Fry and
Söderberg only included two societies from Australia. One, the Tiwi, being the highly violent outlier of their dataset which they exclude from some analyses and the other, the
Aranda, being noticeably non-warlike (Fry & Söderberg, 2013a). Besides the response by
Gat that Fry excluded ethnographic evidence that counters his peaceful characterization of the Aranda (Gat, 2015), broad surveys of ethnographic and archaeological evidence of
Australian hunter-gatherer societies paints a different picture. Allen (2014) contends that his broad survey of paleopathological evidence from the archaeological record, the ethnohistorical record from contact era reports, and later ethnography, substantiate that violent conflict and warfare predate colonial contact in Australia and likely extends back to at least to the late Pleistocene.
Despite the lack of inclusion and consensus regarding these Australian cases, the issue remains unresolved. MFBS neighbored by non-MFBS are in the sample, which is curious considering symbiotic trade relationships between MFBS and their farming or herding neighbors often result in reduced levels of conflict between them, as
27 interdependence among groups is generally noted to foster peaceful relations (Fry, 2012).
As LeBlanc observes, many MFBS that possess these inter-societal relationships were included in Fry and Söderberg’s (2013a) sample, such as the !Kung, Hadza, Mbuti,
Semang, and Vedda (LeBlanc, 2014). Considering their objective of deriving the relative rates of interpersonal and intergroup violence among foragers before the Pleistocene and their understanding of the attenuating relationship of inter-societal exchange relationships on coalitional violence it is problematic that those societies were included in their sample.
Additionally, Bowles (2013) identifies the outright omission of relevant killings for the
Andamanese as a concern; the only south Asian foraging society in their sample not surrounded by non-foragers (LeBlanc, 2014). Specifically, Bowles discovered in his own review of Fry and Söderberg’s source on Andamanese violence four deaths due to coalitional raiding by the Jawara against other Andamanese foraging groups (Bowles,
2013; Radcliffe-Brown, 1922).
A related concern is why are the highly mobile foragers of marginal environments considered the evolutionary analog for the types of societies that humans spent most of their evolutionary history in? Fry and colleagues posits that “the nomadic forager lifestyle most closely resembles the subsistence mode and social organization of the evolutionary past of the Pleistocene” (Fry & Söderberg, 2014, p. 257). Though they acknowledge that
“simple current-day hunter-gatherers are not identical to ancestral groups” but they do serve as our best “windows to the past” (Fry, 2007, p. 197). However, alternative lines of thought hypothesize that as forager groups initially migrated out of Africa they would have primarily occupied the most accessible and resource rich environmental niches encountered (Roscoe, 2014), and it’s these groups that likely originally evolved more
28 complex forms of sociopolitical organization (Marean, 2016). This is critical considering that complex and sedentary hunter-gatherers are known to experience considerable coalitional violence (Maschner & Reedy-Maschner, 1998). It is likely that these more sedentary groups annihilated or displaced other forager groups into those marginalized habitats such as deserts, artic regions, and dryland tropical forests that extant MFBS occupy (Roscoe, 2014). There are opposing evidences to this in that a cross-cultural sample of societies found comparable levels of habitat productivity between foragers and other agriculturalists (Porter & Marlowe, 2007). However, there is reason to suspect that a mobile foraging adaptation to dryland tropical forests is difficult (Roscoe, 2005, 2014) and it’s noted that when the prior analysis is restricted to foragers not in rainforest environments they are found to occupy much less productive habitats (Porter & Marlowe,
2007; Roscoe, 2014). It is notable that when foragers do occupy productive wetland forests, e.g., foraging groups of New Guinea, they are found to be more sedentary and live in larger communities of greater population densities (Roscoe, 2005, 2014). And when foragers do specifically occupy dryland tropical forests it’s thought that they likely relied on exchange relationships with outsider food cultivators in the past like they commonly do in recent times (Headland, 1987). Considering these points, it is quite plausible that a nomadic foraging adaptation to marginal environments either represents an atypical Pleistocene subsistence strategy or a post-Holocene subsistence strategy that relies on exchange with outside groups to buffer the risks of subsisting in these marginal environments. Both however would diminish the relevancy of these groups as the best analogs of the hunter-gatherer societies relevant to human evolution. However, Fry and
Söderberg (2014) state that “almost without exception, complex foragers arose, at the
29 earliest, just prior to the agricultural revolution in locations where adequate marine or other harvestable resources could support sedentary populations” (p. 256), though they provide no citations in support. In response to the general question of whether “nomadic foragers [can] make war?” they respond “Yes, especially under scenarios of crowding and intrusions, which are relatively recent (i.e., not long-term evolutionary) conditions”
(Fry & Söderberg, 2014, p. 256).
Is there reason to believe that the advent of complex and sedentary hunter- gatherer societies and agriculture where nearly simultaneous, or might have sedentism been variable among hunter-gather groups throughout the Pleistocene? I review evidence here that there was and importantly show that these societies experienced the relevant conditions that Fry and Söderberg (2013a) argue leads to more prevalent warfare. A critical aspect of reduced nomadism and increased sedentism and territoriality is the occurrence of exploitable, dense, and predictable resources. A recent archaeological review of Pleistocene African hunter-gatherer resource exploitation summarized that intertidal foraging areas on the southern and northern coasts as well as in riverine and lacustrine ecosystems would have been sufficiently dense and predictable to have been economically defendable (Marean, 2016). In support of this, increasing proportion of diet based on fish is known to negatively correlate to a significant degree with the number of residential moves by a local group per year (Marlowe, 2005), which further substantiates that aquatic resources are sufficiently economically defendable to result in increased sedentism. The oldest known evidence of the utilization of dense and predictable aquatic resources is found at Pinnacle Point (a series of south African cave sites) and is dated to
162 kya (Marean et al., 2014). Pinnacle Point is also considered significant site in that
30 early evidence for the emergence of several features of modern behavioral complexity have been found there. These include an early example of red ochre pigment possibly used in a symbolic manner (Marean et al., 2007), as well as the earliest known evidence of treating stones with fire to facilitate more complex stone tool production (Brown et al.,
2009). Additional evidence of Pleistocene sedentism and the use of aquatic resources across African regions and sites is presented by Marean (2016, p. 7) in Table 2 of his article. Currently, there is no known evidence of warfare at these sites, though it is noted that the required large sample of skeletal remains needed to assess rates of interpersonal and coalitional violence is absent (Marean, 2016). However, what has been shown is that sedentism was highly likely to significantly predate the Holocene and that sedentary hunter-gatherers are known via the archaeological and ethnohistorical record to generally exhibit greater levels of intergroup violence (Maschner & Reedy-Maschner, 1998).
Roscoe (2014) specifically argues that the sedentary and semi-sedentary hunter- gatherers of New Guinea offer underappreciated insight into the pre-Holocene dynamics of intergroup violence. When Roscoe (2014) reviews the ethnographic record of these groups from contact era New Guinea, he states the they exhibit several differences that would likely have made hunter-gatherer warfare more common before the Holocene.
New Guinea foraging societies exhibit communities of greater size, closer residential proximity, much greater population densities, and are more sedentary than nomadic foragers as well as many instances of coalitional aggression between them (Roscoe,
2014). This discussion supports that Fry and Söderberg (2014) are incorrect in their assertion that sedentary hunter-gatherer groups wouldn’t have been present until shortly before the Holocene and this position likely means that they have underestimated the
31 prevalence of coalitional aggression and its effect on human evolution. This being the case then how we frame ethnographic analogy in regards to hunter-gatherers and intergroup conflict needs to be reformulated. The relevant social context of pre-Holocene forager lifeways in regards to understanding the prehistoric emergence of warfare likely no longer exists. However, if such a context did exist it might be populated by a continuum of solely forager groups from highly nomadic to fully sedentary of varying population densities. What would be interesting to know is the relative frequency of nomadic to semi-sedentary and fully sedentary hunter-gatherers throughout the
Paleolithic, and how this relates to climate patterns and global resource distributions. If this could be known, then a more informed assessment of violence and intergroup conflict in the Pleistocene could be inferred from proper ethnographic analogy.
Considering this understanding of the relevant types of social organization pertinent in investigating the prehistory of warfare many of Fry and Söderberg’s (2013a) theoretical underpinnings of a peaceful past are undercut and coalitional aggression is entirely reasonable as a sufficient factor in effecting the evolution of social behavior.
Mechanisms of Coalitional Aggression
With the importance of coalitional aggression in the evolutionary past established how exactly did evolutionary dynamics affect the emergence of these behaviors? The cultural ecology research program holds that pre-state warfare is a mechanism of population regulation which functions to sustain critical resources (Divale, 1970). The most well-known arguments have been specifically focused on the relationship between warfare and the overharvesting of game and subsequent protein scarcity. Where warfare is seen as a mechanism for the creation of game reserves in the dangerous border zones
32 between two conflicting communities (Bennett Ross, 1988; Divale & Harris, 1976).
Because individuals become averse to mount hunting expeditions into these no-man’s- lands protein dense and large animal species are able to repopulate after being overhunted. Critiques of this general research are numerous. One is that pre-contact population levels in the Amazon where likely larger than previously published estimates, introducing doubt that protein was a critical limiting factor in population or community size (Beckerman, 1979). Another is that there are many non-animal sources of highly quality protein available for consumption (Beckerman, 1979). Also critical are issues of alleged unfalsifiable claims. Chagnon and Hames respond to cultural ecological proponents, who argue that both greater and lesser availability of game and protein consumption as support for the cultural ecology theory of Amazonian warfare, that any scientific endeavor must resist post-hoc rationalizing of unpredicted data as supporting a favored theory (1980).
Another established research trend, utilizing mathematical models of genetic and cultural group selection, has produced theoretical support for the coevolution of in-group altruistic behaviors in the context of aggressive between group conflict, often termed parochial altruism (Choi & Bowles, 2007). An analysis of ethnographic and archaeological sources conducted by Bowles revealed that the mortality rate from intergroup conflict would have been sufficient enough to constitute a considerable group- level selection pressure for in-group altruism and out-group hostility (Bowles, 2009).
These high-levels of Paleolithic intergroup violence he notes, are likely instigated by a highly variable global climate and the resulting natural disasters and resource shortfalls, and would provide an explanation for the slow population growth seen from 120–20 kya,
33 given that foraging societies under peaceful conditions have been observed to exceed a growth rate of 2% per annum.
In a regional survey of ethnographic data from New Guinea, Soltis, Boyd, and
Richeson (1995) support mathematical models of cultural group-selection with derived rates of group extinction, group formation, and variability among groups of cultural traits.
Given these data, they conclude that cultural group-selection could produce a group beneficial trait in the time scale of 500–1,000 years and therefore be important in the process of long-term human societal evolution. It is important to note that the societies sampled in this research practiced horticulture, and therefore are not representative examples of the societies that comprised the social landscape in which most human evolution occurred. Additionally, as noted above, even if behaviors are individually costly and group beneficial, an “altruist” can be acting to maximize individual benefit given the inherent benefit of being a member of the group. In the context of coalitional aggression this would likely be a salient consideration. If failure to act cooperatively in inter-group competition results in possible group extinction, then whether or not contributing to group security results in lower life time fitness than other in-group members it would be much higher than the fitness consequences of being in an unprotected group with a higher risk of becoming extinct.
Alternative evolutionary explanations place importance on the individual-level costs and benefits associated with participation in inter-group aggression (Gavrilets &
Fortunato, 2014; Glowacki & Wrangham, 2013). Particular interest is afforded to culture- specific individual rewards for participation in intergroup aggression such as gained status (Patton, 2000), acquired mates (Chagnon, 1988), and potential exchange
34 partnerships (Macfarlan et al., 2014; Patton, 2005; Wiessner, 2006). However, it is argued that this research has not yet produced a definitive conclusion whether more active participants in coalitional aggression universally accrue greater benefits than less active participants. Beckerman et al. (2009) report that they do not for Waorani warriors—wherein the most prolific killers have less reproductive success than less active warriors. In contrast, Chagnon (1988) reports that Yanomamö men who kill in raiding activities, who then acquire the culturally significant label of unokai, have greater success in acquiring wives and producing children than those who do not kill, or the non-unokai.
Similarly, Patton (1996, 2000) establishes the importance of in-group status acquisition for Achuar and Sápara men, and the resulting reproductive benefits, as a motivating factor of strategic violence against competing coalitions. In other words, only violent conflict that advances the interests of an enduring social group should be rewarded by members of the benefitting coalition (this particular context of individual and coalitional violence is more extensively detailed in the ethnographic context chapter below). Thus, if the Waorani data is examined given this understanding then the lower reproductive success of the extremely active killers is more comprehensible; since the observed rates of violence are unique in that 39% of female deaths at all ages are attributable to violence inflicted by another Waorani (Beckerman et al., 2009). Rates of violence this high against women are much less likely to achieve coalitional goals; especially considering rates of violence towards women in other societies were warriors benefit from violence are much lower. For example, for the Yanomamo only 15% of the victims of violent deaths are women and the Achuar, where women constitute 31% of the victims of violent deaths
(for a review of comparable data from 11 lowland South American societies see: (Walker
35
& Bailey, 2013)). These discrepancies should be acknowledged and are better understood as an argument for the rewarding of proper “war heroes” not just “loose-cannon homicidal maniacs”; it is expected that provisioning of status for aggression occurs only when it functions as an instrument of coalitional interests, and the reproductive success derived from such, should only occur if it benefits those who bestow prestige to warriors.
This argument might constitute a second-order collective action problem, in that reciprocation of status to warriors motivates coalitional aggression but if status is individually costly to provision then why should individuals pay the cost when they could free-ride and still enjoy the benefits of being in a group of effective and prestigious warriors? This may not be of such a considerable concern when the status-for-warriorship dynamic is viewed as an iterative process. As Patton (2000) notes, status is only allocated to warriors of the same coalition, that is, to those whom other individuals are allied and are likely to support in future conflicts. From this perspective, the exchange of warriorship for status is characterized by the dynamics of reciprocal altruism in iterative interactions and is therefore not subject to the concerns of the second-order collective action problem (J. Q. Patton, personal communication, Fall 2014).
Additionally, a widely-acknowledged misstep occurred in the comparisons of the
Waorani data, in that Beckerman did not report any comparisons of the most active and less active warriors with non-warriors at all. So, it could be the case that the less
“zealous” warriors accrue greater reproductive benefits than the non-warriors or that averaged together both classes of warriors have greater fitness than non-warriors. The definitions of a warrior were constructed from an individual’s rate of raiding being greater in contrast to the mean rate of raiding of all men, being greater than the mean rate
36 plus one half a standard deviation and exhibiting a rate of raiding a full standard deviation above the mean. As the definition of warrior becomes more and more “zealous” their proxy measures of fitness become less significant across more categories
(Beckerman et al., 2009). Glowacki and Wrangham (2015) contribute to the debate with analysis of patterns of participation in inter-tribal cattle-raids in an east African agro- pastoralist society. They report that raiding activity is correlated with reproductive success in elders who were prolific raiders as youths but not so in a group of non-elders.
Also, this correlation was only seen among elders and raiding but not among elders known to have participated frequently in the riskier large-scale battles that also occur.
The authors consider the cultural institution of bride price as relevant to this pattern of delayed benefits; young men in a family contribute raided cattle to their family’s collective herd and in exchange receive rights to cattle to be used in the future for paying bride price, as older brothers need to be married first (Glowacki & Wrangham, 2015), though it is important to note that the lack of comparison of rates of reproduction between living and dead cattle-raiders leaves the question of how absolute levels of reproductive success are affected unanswered (Zefferman, Baldini, & Mathew, 2015).
This is a similar concern others have noted of Chagnon’s data. Unokai have been shown to have more wives and children than non-unokai (Chagnon, 1988), but if acquisition of unokai status is sufficiently risky, with a great enough risk of mortality then it is possible that the reproductive benefits of unokai are offset by those who die attempting to achieve unokai status or are killed in revenge (Ferguson, 1989b). This is a legitimate concern, but consideration of the data shows that it is not a significant one. Chagnon calculated from his extensive fieldwork and data from the Yanomamo only 5% of raiders were ever
37 injured or killed, with most of this 5% being non-mortal wounds (Chagnon, 2009). This is also supported by the Waorani data, as collected via interviews and published by
Beckerman (2009), that among the interviewees not one ever recollected an attacker being killed in an ambush or raid.
Inter-Individual Differences and Collective-Action
The critical origin from which much of the scholarship on collective action followed was Mancur Olson’s monograph The Logic of Collective Action (1965). In this work Olson distilled three critical points regarding inter-individual dynamics and the collective outcomes of groups; (a) a paradox exists in that the larger a group is the less its individuals will invest in provisioning a collective good; (b) the individuals who stand to benefit the most from the results of successful collective action disproportionally invest more effort into its production; and (c) incentives can be individually targeted, via rewards and punishment, to alter the costs and benefits to overcome the free-rider problem (1965). It is this second point, on the potential disproportionate benefitting and investment in collective action, that this thesis investigates.
It has been broadly theorized and evidenced from computational behavioral models that individuals who have higher stakes in collective success, who have lower costs in contributing effort, and or have greater capabilities or initial endowment of relevant resources can be individually incentivized to contribute and overcome the collective action dilemma (Gavrilets, 2015). More specifically, potential categories relevant to inter-individual variation in the cost-benefit structure of collective action includes leadership propensity, physical condition, skills and knowledge, personality,
38 wealth in resources, and as importantly identified in this thesis, social support (Glowacki
& von Rueden, 2015; von Rueden, 2011; von Rueden, Gavrilets, & Glowacki, 2015).
The most significant component of this emerging body of literature, at least to this thesis, is research on how individual differences motivate group cooperation in service of conflict with other groups (Gavrilets & Fortunato, 2014). Inter-individual differences are proposed to alter the cost-benefit structure of between-group competition if certain individuals have less relative costs associated with contributing, if they have greater strength, skill, or physicality then engaging in aggression could be less costly to them.
Their computational model shows that the collective action problem can be overcome when there is within-group inequality of social rank and that individuals of high-rank, defined as those who accrue greater than equal shares of benefits from collective-action, can be motivated by self-interest to expend effort in between-group conflict (Gavrilets &
Fortunato, 2014). Here it is argued that this conception of social rank is highly consistent with the anthropological construct of social status, namely the relative access to contested resources in within-group interactions (Henrich & Gil-White, 2001; von Rueden, Gurven,
& Kaplan, 2008).
Evidence from Economic Experiments
This thesis utilizes an experimental economic games approach to understand cooperation and competition. Behaviors expressed in experimental games are considered to reflect analogous cooperative scenarios and outcomes from the everyday social interactions of the participants (Henrich et al. 2005). Utilizing this broad class of methods, research concerning inter-group conflict has previously facilitated cooperation in laboratory and field experiments in certain contexts (Bauer, Cassar, Chytilová, &
39
Henrich, 2013; Burton-Chellew, Ross-Gillespie, & West, 2010; Gneezy & Fessler, 2012;
Tan & Bolle, 2007; Voors et al., 2012). Burton-Chellew et al. (2010) found when college students in the United Kingdom played a PGG with competition against another group they were more cooperative than those individuals who played without competition against another group. Tan and Bolle (2007) were able to conclude from their research that cooperation in a PGG increased when in competition with another game group for an additional monetary incentive. This was also the case in a condition with competition between groups that lacked the monetary incentive; cooperation increased even when participants were merely primed that their group performance was going to be compared to the rival competing group before playing (Tan & Bolle, 2007). Moreover, in an experiment with a sequence of conditions involving a team game similar to a traditional
PGG, “lethal” between group competition, where the group with the lowest collective payoff was eliminated, was found to increase cooperation with other group members in contrasts to conditions where elimination was random or absent (Egas, Kats, van der Sar,
Reuben, & Sabelis, 2013)
In ethnographic contexts experimental games have been deployed to investigate the cross-cultural validity of competition as a motivating factor behind cooperation. In
Burundi, individuals who were effected to a greater extent in prior Hutu-Tutsi ethnic conflict were reported more likely to cooperate with an anonymous community member in a dictator game, an economic experiment in which one player determines how an endowment of money is to be divided with another player (Voors et al., 2012).
Additionally, Israeli senior citizens were reported as more likely to reject unfair offers in an ultimatum game, an offshoot of the dictator game where player two can accept the
40 proposed division of the endowment or reject it causing both players to receive nothing, during the 2006 Israel-Hezbollah war than before or after the conflict (Gneezy & Fessler,
2012). In addition, two populations recently exposed to warfare, in Georgia and Sierra
Leone, teenagers, but not children or adults, were more likely to be egalitarian in a sharing game to in-group than to out-group members (Bauer et al. 2013). However, as
Silva and Mace (2014) note, these studies are limited in their explanatory power due to their methodologies. First, while experiments are conducted in a general setting of conflict they are not always competitive or occur between the actual individuals from the groups in conflict, they instead rely upon abstract group categorizations, using children from different schools, senior citizens from a common ethnic group, or anonymous neighbors. Additionally, it is questionable whether the Israeli senior citizens were behaving more cooperatively during the period of conflict rather than spitefully, considering that rejecting ultimatum game offers imposes a cost on both players. Second, a majority do not differentiate between cooperation targeted toward the in-group in comparison with a neutral or rival group. Third, while useful, dyadic games provide measures that are not as relevant to multiplayer dynamics as other experimental games or computation models are, such as the PGG (Gavrilets, 2015).
While this previous research has established between-group competition as a factor in increasing in-group cooperation in the PGG utilizing slightly varying methodologies, inter-individual differences are not usually incorporated into experimental designs (Burton-Chellew et al., 2010; Egas et al., 2013; Tan & Bolle, 2007).
However, there is some preliminary evidence from research that supports group differences can explain variation of cooperative behavior with other group members in
41 competitive contexts (Probst, Carnevale, & Triandis, 1999; Silva & Mace, 2014;
Simpson, Willer, & Ridgeway, 2012).
Silva and Mace (2014) report in the context of Protestant-Catholic conflict in
Northern Ireland individual socioeconomic status best explained variation in overall cooperative behaviors; individuals who were wealthier and had more children were more cooperative in making charitable contributions and returning ‘lost’ letters planted by the researchers, to their respective in-groups. While individuals with higher-levels of education made more charitable contributions to out-group schools, however, there was no effect of participants’ perceptions of conflict on cooperation with in-group members
(Silva & Mace, 2014). Additionally, in research utilizing an n-person prisoner’s dilemma game more individualistic players responded more cooperatively in contexts of between- group competition than in a non-competitive condition (Probst et al., 1999). Also, in research utilizing an experimental PGG participants contributed more to the collective good when they were placed in a high-status condition in comparison to those assigned to a low-status condition, status being primed by informing undergraduate students that they were either interacting with high school students (high status condition) or graduate student group members (low status condition) (Simpson et al., 2012). This collection of research, in addition to the experimental games research in ethnographic contexts reviewed above, provides several conclusions regarding cooperation and competition.
One is that the effect of competition on cooperation is variable, in that individuals can respond varyingly to competitive stimuli and that competitive contexts do not guarantee more cooperation targeted to the in-group, as evidenced by the participants in Silva and
42
Mace’s research who were less helpful to the out-group but not more so to the in-group in situations of greater conflict (Silva & Mace, 2014).
This thesis will build upon this work by designing research that addresses the above limitations; participants are drawn from two naturally formed and sometimes violently competing coalitions in a relevant ethnographic context (i.e., a politically acephalous small-scale society with limited wealth disparities or ascribed status asymmetries), measures of cooperation are derived from an experimental n-person social dilemma game with manipulations to discern cooperative contributions in coalitional and non-coalitional groups in an array of competitive contexts. In conjunction with this approach this thesis also focuses on inter-individual differences in social capital that potentially effect relative costs and benefits associated with promoting participation in inter-group aggression, and collective-action more generally.
Individual Variation in Social Capital
Access to certain kinds of social relationships and the valued resources, information, and obligations that flow among individuals within a population is posited here as potential domain of inter-individual differences relevant to motivations for participating in cooperative between-group competition. These relationships are generally related to the concept of social capital. Social capital has been broadly defined as the features of social networks, like norms or general trust, that allows individuals to more ably pursue their collective interests (Putnam, 1995). An important distinction in the social capital literature concerns the conceptualization of social capital as a property of groups or of individuals within groups (Barr, Ensminger, & Johnson, 2009; Borgatti,
Jones, & Everett, 1998). It is unequivocally a property at both levels of analysis, with
43 each conception having associated strengths and weaknesses. A weakness of the group- level conception and a strength of the individual-level conception is that social capital at the level of the individual is better able to account for intra-societal variation in outcomes of interest (Barr et al., 2009). For this reason, this thesis has restricted focus onto variables of individual-level social capital. These relevant variables of inter-individual differences in social capital are constructed with the tools of social network analysis, which receives attention and explication below.
Social Network Analysis
Social network analysis is an active area of anthropological investigation that examines the informal structure of interpersonal connections and social relationships among individuals in a group or between groups (Borgatti, Everett, & Johnson, 2013). It has recently become recognized as important in understanding the emergence and the nature of cooperation in human groups, given that adaptive mechanisms for the evolution of cooperation involve implicit assumptions of heterogeneity among cooperators and free-riders (Apicella, Marlowe, Fowler, & Christakis, 2012; Nowak, Tarnita, & Wilson,
2010). Cooperators have greater fitness than defectors when they preferentially interact with each other and avoid the cost of interacting with defectors, as defined by the payoffs of a prisoner’s dilemma, and social networks provide a valuable avenue for examining the structure and heterogeneity of these interactions in social contexts. Networks consist of nodes (actors), which are the fundamental entities of some social system, and the specific types of relationships that connect actors together. Basic network theory posits that the positions actors occupy in a network reflect the constraints and opportunities available to them. Especially in regards to ties which function as conduits through which
44 resources, communication, or even diseases flow through a network (Borgatti et al.,
2013). In this thesis social capital is defined and conceived through individual level analysis of social network position, which has become increasing termed as network capital (Borgatti et al., 1998).
Key to this thesis is the concept of network centrality, or the extent to which individuals are structurally important within a network (Borgatti et al., 2013). Centrality has been an evolving concept with a variety of interpretations to its exact meaning and importance, though a notable and stable tenant is that it is a node-level construct (Borgatti
& Everett, 2006). Several related measures of centrality have been developed with slightly different approaches to quantitatively capturing this structural importance and have been used in ethnographic and primatological research concerning cooperative behaviors and reputations (Barr et al., 2009; Bird & Power, 2015; Freeman, 1979; Gilby et al., 2013; Lyle & Smith, 2014). Here I will briefly survey the measures of centrality utilized in this research, more in-depth and ethnographically relevant meanings of these measures will be provided in chapter four. The three centrality measures utilized are known as degree centrality, eigenvector centrality, and betweenness centrality.
Degree centrality is a simple measure that involves summing the total number of edges, or social connections, that any node possess. Essentially, how many others they have a direct connection of a given social relationship (Borgatti et al., 2013; Freeman,
1979; White & Johansen, 2005). Eigenvector centrality is a measure of a node’s centrality as a function of the centrality of other individuals to which they are connected
(Borgatti et al., 2013; White & Johansen, 2005). While betweenness centrality captures structural advantage derived from bridging otherwise disconnected parts of a network and
45 is specifically defined as the proportion of shortest paths that connect each dyadic pair of nodes that an ego node lies upon (Borgatti et al., 2013; Freeman, 1979; White &
Johansen, 2005). While degree centrality only considers the direct interactions that occur between ego and another individuals, eigenvector and betweenness centrality take indirect connections among the individuals to which ego is connected into account
(Brent, Lehmann, & Ramos‐Fernández, 2011).
Broadly, centrality affects differential access and control of information or resources as they flow through a network by certain individuals (Freeman, 1979). This is predicted to affect an individual’s ability to acquire a greater than average share of resources and benefits in within-group interactions, and is therefore relevant to this thesis given its focus on inter-individual variation and cooperation. This ability of individuals to more effectively manipulate information, resources, and relationships in their own self- interest as derived from their position of structural advantage is called gatekeeping
(Barzilai‐Nahon, 2008; Bavelas, 1948; Freeman, 1980). Potential ways gatekeepers might gain advantage “include, among others, selection, addition, withholding, display, channeling, shaping, manipulation, repetition, timing, localization, integration, disregard, and deletion of information” (Barzilai‐Nahon, 2008, p. 1496). A specific instance of this exact phenomena has been noted by Descola (1996) in his ethnography of the Achuar in the Ecuadorian Amazon, also the context of this study, when he states that “news . . . tends to be systematically distorted as it is carried from one house to another by a series of different visitors. These messengers . . . interpret the facts to suit their own personal interests (p. 63). Past research at the field site has established methods and theoretical importance in collecting data amenable to network analysis, given its role in explaining
46 cooperation in the ultimatum game, over time and across several communities (Patton,
Zerbe, & Peñaherrera-Aguirre, 2016).
Other ethnographic research has also shown the importance of network positioning using a variety of centrality measures in regards to mechanisms that favor cooperative behavioral strategies (Barr et al., 2009; Bird & Power, 2015; Lyle & Smith,
2014). In the context of prosocial reputation signaling among the cooperative hunting
Martu of western Australia, greater generosity in sharing meat (as a percentage of total amount of meat harvested) predicts both a hunter’s eigenvector and degree centrality in a cooperative hunting network (Bird & Power, 2015). Lyle and Smith in their examination of benefits of cooperative reputations in the Peruvian Andes found that more cooperative individuals developed reputations that facilitated larger social support networks, via degree centrality, which helped buffer against stochastic health risks (Lyle & Smith,
2014). Another study found that social entrepreneurs, those with greater degree and betweenness centrality, were more trusting of others in two study populations and in one of those populations, the Orma of Kenya, they were more trustworthy in an experimental trust game (Barr et al., 2009). The authors interpret these results to establish that social or political entrepreneurs are opportunistic risk takers. Risky in the sense that they take opportunities to trust others in hopes of forging new beneficial social relationships and thus achieving positions of high centrality in a social network, even though the potential cost of being defected upon is present (Barr et al., 2009).
A primatological study provides support specifically for the importance of centrality in motivating coalitional cooperation. Gilby et al. (2013) conducted an analysis of the social network centrality and its potential social and reproductive benefits among
47 the wild male chimpanzees of the Kasekela community at Gombe. They found that greater betweenness centrality in a coalition network was associated with an increase in social dominance rank while also being positively associated with a greater probability of siring offspring during the study period independent of dominance rank. Though these outcomes were not found to hold in regards to the effects of degree or eigenvector centrality (Gilby et al., 2013). This suggest that Chimpanzees recognize third-party relationships and utilize this information to create alliances to position themselves into individually beneficial and structurally important roles within their local network of alliance relationships and potentially influences our understanding of the evolution of social intelligence.
It has been broadly shown that network centrality is an aspect with which individuals vary, is relevant to cooperative behaviors and outcomes in an array of contexts, both in humans and our closest primate relatives, and that individuals are willing to take risks and potential costs to access more centrally located network positions. Given these observations, centrality measurements are appropriate variables in analyses concerning individual differences that effect cooperative outcomes. Further, they’re likely to affect the evaluation of the costs and benefits associated with cooperation so that cooperation is in an individual’s interest if it is in service of maintaining their advantageous position and social relationships. As is likely the case when conflict and group competition can have serious impacts on the maintenance of social relationships and the integrity of social networks.
48
Summary
This thesis seeks to accomplish two broad aims: (a) further elucidate the contexts, group organization and variation in the level of group competition, which triggers greater cooperation within groups; and (b) to test predictions derived from recent theoretical models of how inter-individual differences motivate cooperation in coalitional competition in a relevant ethnographic context. To my knowledge there has been no prior research that collects measures of cooperation among naturally formed and aggressively competing coalitions, in-situ, in an n-person economic game with experimental manipulation to discern the effects of between group competition and coalitional group membership in a tribal society.
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CHAPTER 3
ETHNOGRAPHIC CONTEXT
Introduction, Location, Ecology, and History
This research was conducted, by myself and John Q. Patton in the summer of
2015, in a bi-ethnic tribal community of Achuar and Sápara peoples known as Conambo, located in the Pastaza province of the Ecuadorian Amazon. Geographically, Conambo is positioned at 1° 52.16’ south and 76°52.42’ west and lies along both sides of the
Conambo river, an eventual tributary to the Amazon river, and is approximately 60 miles upriver from the Ecuador-Peru border. Conambo is remote, only accessible by small propeller airplanes, and self-sufficient; there are no markets or monetary transactions for goods. Social complexity is limited and is usefully summarized by Murdock and
Provost’s (1973) cross-cultural classification system which identifies the Jivaro generally as lacking many traits of cultural complexity. This riverine environment and the surrounding interfluvial region is characterized by a climate that experiences an immense amount of rainfall; roughly 2–3 meters annually (Descola, 1994), extreme humidity and little seasonal variation (Service, 1978). Altitude fluctuates from approximately 400 m to
250 m above sea-level for the hills and alluvial valleys that characterize this topography, with an annual average temperature of 74°F (Descola, 1994). This region is also noted as unique in possessing exceptional biodiversity (Myers, Mittermeier, Mittermeier, Da
Fonseca, & Kent, 2000).
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Social Organization and Demography
Conambo is comprised of spatially separated and independent households of extended families or of small clusters of nearby households which are usually related.
Households, or these residential clusters, are connected by a series of trails usually with no line of sight between residences. There is considerable coalitional division in the community as households are politically affiliated as either Achuar or Sápara and segregate among themselves either upriver or down river in relation to the airstrip in the community center respectively (see Figure 3).
Figure 2. Typical distribution of Achuar and Sápara households in Conambo. Adapted from “From Pottery to Politics: An Ethnoarchaeological Study of Political Factionalism, Ethnicity, and Domestic Pottery Style in the Ecuadorian Amazon,” B. J. Bowser, (2000), Journal of Archaeological Method and Theory, 7, p. 225.
The people of Conambo, like other communities of Sápara, Achuar and other
Jivaroan groups, are politically egalitarian, in that men and women achieve positions of relative status through their actions in certain behavioral domains. Men notably strive to achieve social status through developing a reputation as a formidable warrior (Harner,
1984; Kelekna, 1994; Patton, 1996, 2000; Service, 1978). With informal leadership
51 positions emerging in contexts of warfare; wherein a fortified settlement voluntarily comes under the aegis of a ‘great-man’ or juunt (Descola, 1994). Warriors further their reputations as a nearly invincible and powerful individuals, or kakaram, through the successful organization and conducting of assassination raids against enemy settlements
(Kelekna, 1994). This is in contrast to positions of hierarchical status that are ascribed to certain individuals by virtue of their membership in a particular kinship lineage or heredity position, as is the case with more hierarchical societies (Murdock & Provost,
1973).
The Achuar and Sápara of Conambo and surrounding areas are primarily characterized by a matrilocal post-marital residence pattern and out group exogamy.
Young men are often expected to move into and reside in the house of their father in law after marriage. And historically, comprise a significant contingent of organized raiding parties organized by their father and brothers-in-law (Kelekna, 1994). After some time of service to his affinal household a married man and his wife will establish their own independent household. However, descent and kinship ties are often reckoned bilaterally, but with a patrilineal bias (Patton, 1996).
At the time at which this research occurred the total population of Conambo was roughly 200. Unlike the traditional pattern of polygamy, the men and women of
Conambo are mostly monogamous, though fertility is still high and childhood mortality is low (Patton, 2005). Reproductive success in Conambo is comparable between the sexes; women have an average inter-birth interval of 2.4 years and have around eight children during their reproductive careers, while the men of Conambo on average have nine children during theirs (Patton, 1996, 2005).
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Subsistence Pattern
The most important subsistence activity that people engage in is that of slash and burn horticulture and the cultivation of garden crops, the most notable being the manioc tuber, Manihot esculenta. Supporting this importance is the incredible intensity at which manioc cultivation as compared to other plant species occurs, as evidenced by the observations of Boster (1983) among the gardens of Aguaruna and Huambisa (other
Jivaroan tribes) women. Garden production is squarely in the realm of women’s production activities and accounted for between 71.3 to 91.5% of daily consumed calories in the Achuar households as sampled by Descola (1994). In additional support,
Ross and colleagues (1978) report that 74.7% of per capita daily food bulk is accounted through horticulture production in their sample. An important use of manioc is in the production of chicha, a slightly fermented beer, made from the masticated pulp of steamed manioc which is subsequently stored and fermented. Chicha is valuable alone as an energy source, but is also notable as an integral aspect of welcoming visitors to a household and in the politicking of alliance formation among men.
In addition to grown food, hunting and foraging of faunal resources is quite critical in the subsistence of the people in this region. Approximately 51.7% of daily per capita protein consumption is sourced through hunting activities, which accounts for
17.4% of all daily calories consumed per capita (Ross et al., 1978). Men are the predominant hunters and target many small to mid-sized animal species; which include white-lipped peccary, agouti, armadillos, tapir, deer, various monkey and bird species, and other rodents (Kelekna, 1994; Patton, 1996; Ross et al., 1978). Traditionally, spears were used in harvesting larger ground and blow guns with poison-tipped darts used to
53 hunt arboreal-dwelling species. Later the introduction of crude muzzle-loading shotguns and black powder lead to their adoption as the hunting weapon of choice (Patton, 1996).
However, given the current difficulty in acquiring these munitions due to levied taxes, blow-gun hunting is once again the norm (J. Q. Patton, personal communication, Summer
2015).
Subsistence needs are also partially met through the capture of riverine resources which constitutes approximately 26.4% of daily consumed protein and is practiced by both men and women (Kelekna, 1994; Ross et al., 1978). Various fish species are harvested via hook and line, such as piranha, catfish, and freshwater stingrays; further river turtles and their eggs are often sought and consumed (Patton, 1996). A few of the methods and tools implemented include traps, spears, lines, nets, and weirs (Whitten,
1976). Additionally, the collective task of barbasco fishing, or communal fish poisoning also takes place. Wherein, the barbasco is dumped into an area of a stream and the resulting stunned and intoxicated fish are easily scooped up or speared at the surface at a site down river (Gill, 1940; Harner, 1984; Whitten, 1976).
Recent History of Violence in Conambo and Surrounding Areas
Critical to this thesis is the understanding of the patterns of aggression and violence that occur in Conambo and surrounding areas. This region in particular, and
Amazonia in general, has long been a focal point in the scholarship of tribal warfare
(Walker & Bailey, 2013). Established patterns of violence take the various forms of feuding, raiding, and homicide as well as having but a few salient motives. Among the
Jivaro in general, and the Shuar and Achuar in particular, homicide is often the recourse to personal instigations involving competition over women, such as wife seduction,
54 stealing, infidelity, etc. and is considered appropriate punitive action (Harner, 1984;
Kelekna, 1981). These types of occurrences, along with perceive magical attacks via witchcraft, are the impetus for cycles of violence (Kelekna, 1994). As noted by various sources seeking revenge for prior violence is an immediate motivation for retaliatory action, which themselves evoke violent responses from the victims and their families
(Boehm, 2011; Kelekna, 1981). Specifically, as recounted by Kelekna, personal vendettas and assignations lead to quickly shifting alliances and feuding and warfare among households and settlements (1981). In this way feuding becomes a runaway social process that has understandably lead to the high rates of death due to homicide and warfare in this region.
Feuding and warfare has been observed to occur at various scales of social organization. From intra-village violence, between different factions of a single community, to intra-tribal violence between different communities, and inter-tribal warfare (Gill, 1940; Walker & Bailey, 2013), all of which has been observed among all the Jivaroan tribes, like the Shuar and the Achuar (Harner, 1984). Also at times conflict between a federation of Jivaroan tribes and communities against socially distant outsiders, such as the Inca and then the Spanish, has been observed (Harner, 1984;
Service, 1978). One recent instance of coalitional aggression occurred when a coalition of
Achuar and Sápara from Conambo traveled down river and held another community at gunpoint and burnt down their village. This encroaching community of either Shiwiar or
Quichua—other related ethnic groups, where perceived as a social threat and the separate political coalitions that comprise Conambo effectively coordinated a joint venture to resist them (J. Q. Patton, personal communication, Summer 2015). Since the founding of
55
Conambo, in 1978, five known homicides have occurred (J. Q. Patton, personal communication, Summer 2015).
Thorough interviewing by Patton in his initial trip to Conambo revealed a recent statistic of 50% of male deaths due to homicide and feuding (1996). This parallels other surveys and calculations of the frequency of violence in nearby areas of the same period.
Jane Bennett Ross (1984) notes that Achuar men that reside along the Morona river in the
Peruvian Amazon have a mortality by homicide rate of 59%. And that 27% of Achuar women of the same area died by homicide. Additionally, another calculation of rates of violence is in agreement with this general approximation of 50% of male deaths due to violent conflict (Taylor, 1981) These data establish that the Achuar experience the second highest rate of homicide due to violent conflict in the entire world, only surpassed by the
Woarani who’s traditional territory encompasses an area just north of the Achuar along the Curaray and Napo rivers (Beckerman et al., 2009).
Achuar and Sápara Ethno-histories
Though the Achuar and Sápara of Conambo share most aspects in common in regards to subsistence behaviors, social organization, and cosmology there are several details in which they diverge. One primary difference is in language. While both groups speak Spanish to an intermediate extent as a second language they speak different indigenous languages. The Achuar speak the Achuar language and the Quichua language; the latter now considered the indigenous lingua franca of much of Western Amazonia and
Andean regions. While the Sápara only speak Quichua in addition to Spanish but hardly any Achuar. Another difference is seen in the minute variations in stylistic patterning that adorn their respective pottery traditions (Bowser 2000). House structure is another realm
56 of difference. The Achuar build oval-shaped thatched roof houses while the Sápara have adopted an A-frame design for their homes. Additionally, while both groups utilize blowguns in the hunting of prey species it is noted that only the Achuar engage in their manufacture, producing them from the conjoined halves of the straight-grained and naturally hard chonta wood. The blowguns that the Sápara use are all originally made by
Achuar and are acquired through some trade or other exchange relationship with them.
While Achuar and Sápara peoples have come together to co-settle the community of
Conambo they have distinct histories of ethnogenesis and migration.
Achuar History
The Achuar are one of the several cultural subgroups of the larger Jivaroan ethnolinguistic group, the others including the Shuar, Aguaruna, and Huambisa. The
Achuar ethnonym is derived from the Mauritia flexuosa palm (or aguajes), which densely inhabit the common swamps (aguajales) that characterize the ecosystem occupied by
Achuar. Achuar therefore means the “people of the Mauritia (achu)” (Descola, 1994, p. 205).
During the time of his research the Achuar population was approximately comprised of 2,000 people occupying a estimated territory of 12,000 km2, thus achieving one of the lowest measures of population density in Amazonia of 0.17 persons/km2
(Descola, 1994). Though this number has since grown, and the Achuar now claim a population size of approximately 3,000 (J. Q. Patton, personal communication, Fall 2016)
As illustrated in the figure below, the traditional home range of the Achuar spans from the lower Huasaga and Pastaza rivers at the southwestern extent, in both Ecuador and
Peru, and east through the Bobonaza, Corrientes, and Tigre rivers. With the Tigre
57 beginning at the Peruvian border at the confluence of the Conambo and Pindo Yacu rivers, which define the most eastern portion of Achuar territory in Ecuador.
Figure 3. Map of the regional ethnosphere. Adapted from The Spears of Twilight: Life and Death in the Amazon Jungle, P. Descola,(1996), New York: The New Press.
The Jivaro have an incredible history of resistance to attempted subjugation by outside groups. As Service notes in his concise overview of Jivaro history, before the arrival of European explorers, the Incan empire in the 1549 attempted to expand northward into the oriente region where the Jivaroan groups reside (1978). The Inca were unable to conquer Jivaro territory given the fierce resistance that was mounted against them from unfamiliar and inhospitable terrain (Harner, 1984; Service, 1978).
58
The discovery of gold deposits in these headwater regions of the Upper Amazon transpired increased migration of hopeful Spanish miners into the area. The general domination and inhumane practices, including slavery, directed towards the indigenous groups in the region by the Spanish culminated in a destructive and thorough revolt against the Spanish in 1599 (Harner, 1984).
A more recent example of encroaching violence involves the conflict with the
Shuar, another Jivaroan group, to the west. The establishment and closing of the
Ecuadorian-Peruvian border in 1942 by the protocol of Rio de Janiero cut off an important trade route for ammunition and arms. Previously the influx of these resources resulted in a balance of power in the conflict between the two groups (Harner, 1984).
When their ability to procure arms became seriously comprised, the Achuar became increasingly victimized by Shuar, especially in the Shuar drive to produce tsantsas, or the shrunken heads of slain enemies, for the collectables market (Bennett Ross, 1984). In order to escape these hostilities some Achuar migrated east into the Conambo river valley. The current Achuar settlements along the Rio Conambo and Rio Pindo comprise the most eastern extent of Achuar territory.
Sápara History
The Sápara are the result of a long occurring process of ethnogenesis involving the intermarriage of Achuar and Sápara peoples (Patton, 2004; Whitten, 1976). The
Sápara were the original inhabitants of the Conambo river valley and surrounding areas during an intense period when newly introduced diseases and subjugation, including slavery, were wrought by encroaching colonial powers through the sixteenth and eighteenth centuries (Whitten, 1976). The once populous group, estimated to include
59 about 100,000 people was decimated, and approximately lost 60–100% of its former population size (Whitten, 1976). Later on a measles epidemic severely affected the remaining Sápara and initiated a severe period of conflict via feuding and raiding, known as the brujo wars, given that the measles outbreak was a suspected to be malevolent magical attacks (Patton, 2004). It is to this era people refer to as the time when “we were ending” (J. Q. Patton, personal communication, Summer 2015). At the time of Patton and
Bowser’s original research trips, 1992–1994, there were only four known speakers of the
Sápara language remaining in the Conambo river valley (J. Q. Patton, personal communication, Summer 2015).
It was shortly after this time that the Achuar, fleeing the head-taking raids of the
Shuar entered the Conambo river valley. Achuar and Sápara began to inter-marry and households soon adopted the Quichua language as it was the only language in common between the two ethnic groups. The language long before having become a regional lingua franca throughout the coastal, sierra, and oriente regions due to its application in facilitating trade and exchange relationships (Whitten, 1976). Through time these people began to identify as Quichua, though recently there has been a shift back to identifying as
Sápara, and are they referred to as the jungle Quichua culture by Whitten, being the
Quichua that lived in the outlying areas south of Canelos (Whitten, 1976). Though as
Whitten notes, this inter-marrying and co-existing of Achuar and Sápara in general has been a continuing process for centuries and likely extends back beyond the earliest colonial accounts of any groups in the Ecuadorian oriente (1976).
The history of the founding of Conambo is entangled with the history of oil exploration in the area, which began in the early 1970s. At that time, only a few isolated
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Achuar residences where located in the general vicinity of Conambo. After the airstrip was constructed to facilitate oil exploration activities, two Achuar brothers, each the head of their own household, arrived from Alto Corrientes to settle in Conambo. They reportedly moved to avoid already established and persisting conflicts there and soon thereafter additional households and men started resettling in Conambo and marrying in.
Initially one Sápara couple arrived from the community called Papaya to settle
Conambo, and they were soon joined by the households of the man’s two brothers. Over time more families moved in and new households were established by young men marrying in on both sides. Also, several Achuar households have moved downriver from the airstrip and have become politically allied with the Sápara, several times after lethal conflicts. Though these households later fissioned off from Conambo to establish a separate community, which occurred nearly a decade before this study was conducted.
Due to periodic re-alliances and the fluid process of ethnogenesis, as discussed above, two-thirds of the downriver Sápara coalition has ethnically Achuar members and likewise the upriver Achuar are one-third comprised of ethnically Sápara members (Patton, 1996).
Though again, this has changed over time as households move and alliances shift. It should be noted that the social contexts that are reported by Patton (1996) during his dissertation research is not necessarily the social context of Conambo currently.
Additionally, there is variable and flexible identification as Quichua or Sápara by the down-river coalition, though they are referred to consistently as Sápara in this thesis.
Though most can trace their heritage back to full blooded Achuar and Sápara within one or two generations, lending support to the observation that the coalitional division in
Conambo is more political than due purely to defined differences in ethnic heritage or
61 kinship, and must in-part be a factor in the opportunistic nature of alliance formation and coalitional re-alliance (Patton, 1996).
Summary
The most important characteristic to recognize about this ethnographic context, with regards to the aims of this research, is the incredible relevance of coalitional violence in the lives of the people who live in Conambo and the surrounding region at large, both currently and historically. The elder generations of this region still remember the times of incessant warfare and raiding which are aptly referred to as “the times we were ending” (J. Q. Patton, personal communication, Summer 2015). Additionally, the limited social and cultural complexity of the region is a valuable context in which to conduct this thesis research. Settlements are sedentary but impermanent, communities average fewer than 100 people, the region is sparsely populated, they are stateless with non-centralized political authority, and are essentially egalitarian – lacking classes or wealth disparities (Murdock & Provost, 1973).
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CHAPTER 4
METHODS AND HYPOTHESES
This thesis tests hypotheses concerning the influence of social network capital, specifically centrality, in motivating individuals to cooperate in competitive contexts.
Two different social networks were constructed from data via two methods. An information-sharing network was assessed with a traditional network task and a coalition- alliance network was assessed with a top-down pile-sorting technique. Variables of individual network centrality are derived for both information and alliance networks using UCINet 6 (Borgatti, Everett, & Freeman, 2002) and made available for analyses.
Additionally, a measure of cooperation is acquired through the conducting of a public goods game with varying coalitional and competition treatments.
Information-Sharing Network Task
Social network structure is collected by interviewing every adult in the community and recording their responses on a network analysis task. This method produced an information-sharing network that included both the men and women of
Conambo. Specifically, this task involved each participant sequentially examining photographs of all the adult participants in the community in a randomized order.
Participants were asked which of those individuals they trusted enough to solicit information from if an unknown problem were to occur in the community while they were away. Participants were instructed to respond either yes or no for every individual
63 photograph and the participants’ responses were recorded in an interaction matrix of all adult participants in Conambo (1 = yes, 0 = no). From these raw data a number of social network attributes were calculated and made available for further statistical analysis in
SPSS. For each individual in the network an array of variables relevant to in- neighborhood network centrality are calculated: degree centrality, eigenvector centrality, and betweenness centrality. The in-neighborhood distinction means that calculations only involve ties that are directed at ego from other nodes. This insures that a node would not achieve an inflated centrality score because they indicated they would ask a lot of other people for information in the task. Centrality measures reflect central individuals as those individuals who others indicate they would solicit information from and it’s for this reason that our centrality measures are more specifically indegree, inbetweenness, and beta centrality. Eigenvector centrality is substituted by beta centrality to account for the directed and non-value nature of this network matrix (Borgatti et al., 2013).
It is now appropriate to provide ethnographically relevant meanings to these measures of centrality. Degree centrality measures how many people trust ego enough to solicit valuable information from them, indicating that an individual is either trustworthy or has access to important knowledge and is willing to share. Betweenness centrality indicates how able ego is in gatekeeping information, that is, how structurally important they are in connecting otherwise separated sections of the network. This individual could be perceived as having access to information through others that ego doesn’t trust or cannot access themselves. Beta centrality would measure how connected ego is to other individuals who themselves are well connected and trusted by others to seek important information from, that is, they are connected to others who themselves are popular.
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Successive Pile-Sort: Coalitional-Alliance Network
A top-down successive pile-sort method was used to ascertain measures of coalitional-alliance strengths between each dyadic pair. This successive pile-sort method is largely adapted from Weller and Romney (1988), and has been previously utilized in research in Conambo (Patton, 2004). Conducting the successive pile-sort consisted of presenting each participant with a randomly mixed group of ID photos on a table of either all the men or women in the community, including themselves. For this task men and women are only asked to perform the task with the photos of those of the same sex. The participants are asked how people would likely split into different groups if there was a hypothetical community conflict. The participant rearranges the photos into two new and distinct groups to indicate how the split would occur. Then participants are asked to identify which one of these two new groups would be the one that would more easily divide into two more groups by some hypothetical conflict. This process is repeated and every time the participant indicates which group would split and how they would split by arranging the photos a “cut-card” is placed between the piles. Cut-cards have letters written on them and one is placed between two groups every time there is a new split in alphabetical order. In this way, the order of the splits made are retained and recorded.
This provides a measure of the strength of the coalitional alliance between each dyadic pair by assessing the number of splitting events each dyad survived as members of the same group. Further, it should be noted that participants were not forced to divide groups until only single photos remained, but that groups were split only as far as each participant was willing to indicate.
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These data are input into the cultural domain analysis program Anthropac
(Borgatti, 1996) which calculates the aggregated judgments of the participants into a matrix that contains the alliance strength score for each dyad, which ranges from 0 to 1.
These scores can then be summed by coalitional membership to produce each participant’s average alliance strength score within and between their respective in-group and out-group coalitions. This output is further transformed by creating a cut-off point in which every dyadic alliance strength score above it receives a one and every dyadic score below receives a zero. This creates a non-directed but non-valued matrix which is amenable as input into UCINET 6 in order to derive the degree, eigenvector, and betweenness centrality measures in the men’s and women’s alliance-networks (Borgatti et al., 2013). The cutoff point was placed at the mean value of in-group alliance strengths.
The in-group alliance scores are pooled together from both coalitions, allowing for coalitional differences in alliance strengths to remain present. This is done for two reasons. One, in contrast to taking the cut-off as the total average alliance strength (in- group and out-group alliances strengths pooled together), using the in-group alliance mean allows for heterogeneity in the strengths of in-group coalitional alliances to be present. If the total average alliance strength is used then nearly every individual within the two political coalitions are connected with every other in-group member, this homogeneity of in-group alliance relationships makes statistical models that predict cooperation with coalitional members from alliance centrality measures problematic.
Two, if a conflict were to arise between a random dyad within a coalition then those individuals whom share an alliance relationship of above average strength is likely to predict how they will receive coalitional support from others on average.
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In sum, only one mean was used to determine the cutoff point for each alliance network, since men and women are in separate alliance networks their respective mean value of in-group alliance strengths is used for their network. This gives the measures of coalition-alliance network centrality used in subsequent regression analyses. Degree centrality in the alliance network is indicative of the number of other individuals to which ego is tied by an alliance relationship. Eigenvector centrality in the alliance network is indicative of those who have strong alliances with individuals who themselves have greater coalitional support from allies of their own. Which could be important if the quality of the allies to which ego is tied effects decisions of cooperating or defecting.
High betweenness centrality in the alliance-network represents individuals who are allied to others whom themselves are not allied and could derive leverage in brokering political support from others.
Public Goods Game
This research deploys an experimental economic game known as the public goods game. The prisoner’s dilemma as it was traditionally conceived and modeled in the
Axelrod and Hamilton computer tournament was a dyadic interaction among players.
One important difference between that model and actual scenarios of cooperation is that in human social life cooperation often involves more than two people. The incentives for defection and cooperation are the same with multiple players as in the dyadic prisoner’s dilemma; the group payoff is maximized by full cooperation, while the individual payoff is maximized by full defection. The PGG is simply another name for an n-person prisoner’s dilemma (Hardin 1971; Nowak & Highfield 2011), and is used to model the conflict between individual and group interests and provides an experimental measure of
67 cooperation and is amenable to an array of theoretically interesting manipulations
(Camerer & Fehr 2004). Behaviors expressed in experimental games are considered to reflect analogous cooperative scenarios and outcomes from the everyday social interactions of the participants (Henrich et al. 2005). It follows that the introduction of coalitional and competitive motivations into game structure will be informative of patterns of cooperation regarding these same motivations in similar behavioral contexts, i.e., coalitional conflict.
The game includes participants playing in anonymous groups of four participants with each participant being endowed a sum of money with which to make anonymous decisions and play the game with. The PGG consists of deciding how much of their individual endowment they want to keep for themselves and how much they want to contribute into a common-pool, or group pot. The final monetary payoff for each participant includes an equal share of a common-pool, or group pot, after the participants’ contributions have been summed and doubled. In addition to this share of the group pot each participant keeps the proportion of their individual endowment that they didn’t place into the group pot. This creates a payoff matrix where group benefit is maximized by all participants contributing their whole endowments but where individual benefit is maximized by defecting while other group partners contribute. The decision regarding how much, if any at all, of their individual endowments to put into the common-pool provides the measurement of cooperation.
The size of endowments have previously been standardized as one day’s wage in the local economy (Camerer & Fehr, 2004). However, since each participant will play the game five times, each time in a different experimental condition, the endowment size will
68 be half of what can be earned in a day for each treatment a person plays. This is done so that the endowment size is still sufficiently large enough to encourage serious decision- making within the game and so when the individual endowments are summed across all treatments it isn’t such an inordinate of money. Ecuador currently uses U.S. currency. A day’s wage is roughly $5 so for each treatment participants are endowed with $2.50. To play the game participants are brought in to a private room and are explained the game, it’s rules, and are tested for accurate comprehension of the instructions (see appendices A and B for the protocols used). Once comprehension has been demonstrated participants make their anonymous contribution. Participants are presented with a desk with a horizontal line on it. Ten quarters are in horizontal line on the side of the desk closest to them. To contribute to the common-pool participants place however many quarters they want to contribute across the line on to the other side of the desk. Further, this project applies treatments to the PGG structure designed to invoke the effects of coalitional grouping and varying levels of competition on internal group cooperation. Each participant plays the treatments in a randomized sequence. For the purposes of succinctly explaining the logic of the PGG treatments they are referred to here as the first, second, third, fourth, or fifth treatments, though each participant played them in a different and random order.
Treatment one consists of participants playing in non-coalitional groups that include both Achuar and Sápara participants, this functions to register a baseline of cooperation that characterizes the community (noted as non-coalitional group composition and includes two Achuar and two Sápara participants in a group).
Participants’ individual identities are kept anonymous throughout the PGG. They are only
69 aware of the political affiliations of the other participants in their game group. In treatment two of the PGG participants are competing against another game group (of the same non-coalitional group composition) and are instructed that the group whose group- pot contains a greater total amount of contributions will be the winner group and receive a bonus sum to introduce a “spoils of war” incentive. Each participant in the winning group received an additional dollar, which constitutes a 40% bonus. This treatment isolates the effect of competition on group cooperation independent of game groups that are distinctively coalitional.
The next three PGG treatments all have coalitionally organized game groups, which were either four Achuar participants as a group or four Sápara participants as a group. In the third treatment, coalitional groups play a round without competition as the first treatment was conducted. In the fourth treatment, groups are coalitionally organized and in competition with another game group comprised of their same ethnic group members (i.e., an Achuar vs. Achuar coalition or a Sápara vs. Sápara coalition). This treatment provides a level of competition that is akin to intra-ethnolinguistic or intra- coalitional competition and captures the effect of competition on in-group cooperation. In treatment five coalitional groups play the PGG in competition with a game group from across the main coalitional divide. This structures the competition between two out-group coalitions (i.e., an Achuar vs. Sápara coalition) and raises the level of competition to the inter-coalitional level. These last two competition treatments will enable assessment of variation of the level of social organization at which competition occurs on in-group cooperation. See Table 1 for a summary of PGG treatments.
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Table 1. Coalitional and Competitive Conditions of the PGG
Variable aspects of the experimental PGG treatments treatment group composition competition level of competition 1 non-coalitional absent - 2 non-coalitional present non-coalitional 3 coalitional absent - 4 coalitional present intra-coalitional 5 coalitional present inter-coalitional
Hypotheses
Coalitional Effects on Cooperation
Coalitions are thought to enhance cooperation due to the shared genetic relatedness of the individual members. This is often the case in patrilocal societies where males have more and stronger genetic relations in the community than females, who emigrate from some other community (Boehm, 1992; Van Velzen & Van Wetering,
1960). However, recent analysis of variation in cohabitation patterns in hunter-gatherer societies indicates that most co-resident adults that comprise a band are unrelated, with the authors concluding that other mechanisms of reciprocity, reputational effects, or punishment are required to explain the emergence of cooperation in ancestral hunter- gatherer populations (Hill et al. 2011). Moreover, a recent analysis of Hadza social networks indicated that certain individuals possessed a greater share of degrees (social ties) in their network than others and that reciprocity was a significant factor in anonymous resource-sharing after controlling for kinship (Apicella et al. 2012).
Coalitional groups could possibly exhibit greater cooperation than the random groups since individuals would likely have a greater expectation, opportunity, and likelihood of
71 being reciprocated for their cooperation in the future by coalition members than by non- coalitional individuals. These predictions whether rejected or supported will clarify the specific influence of coalitional groups on cooperation in competitive and non- competitive contexts.
Hypothesis 1: In a context absent of between group competition, cooperation will be greater in coalitional groups than in non-coalitional groups.
Hypothesis 2: In a context of between group competition, cooperation will be greater in coalitional groups than in non-coalitional groups.
Competition Effects on Cooperation
A recent review and analysis of data concerning violent death among 11 low-land
Amazonian societies, Walker and Bailey report in instances of external warfare (across an ethno-linguistic boundary) that death totals are significantly greater per violent event than in internal warfare or in intra-village violent conflicts. If number of deaths is related to the amount of effort contributed or risk involved in coalitional aggression, then these death rates could indicate that greater cooperation is involved in such contexts. However, it should be noted that 55% of all deaths analyzed occurred at the level of internal warfare; conflict between separate communities of the same ethnolinguistic group, this indicates that acts of aggression in service of internal warfare are less deadly per event but more frequent. If greater risk is derived from being a more frequent raider, then conflict against other coalitions within a common ethnolinguistic group might also influence higher levels of cooperation.
Hypothesis 3: In a context of non-coalitional groups, cooperation will be greater when competing against another group than when there is no competition.
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Hypothesis 4: In a context of coalitionally organized groups, cooperation will be greater when competing against another group than when there is no competition.
Hypothesis 5: In a context of coalitionally organized groups, cooperation will be greater when competing inter-coalitionally as compared to competing intra-coalitionally.
Social Network Centrality Effects on Cooperation
Asymmetry in social network centrality is generally hypothesized to function as a possible domain of inequality than can affect the cost-benefit structure of in-group cooperation when in competition with other groups. Gavrilets and Fortunato’s model relies upon inequality within a social group as being critical in the subsequent disproportionate usurpation of in-group resources by those with high rank (2014). This being so, centrality would unlikely be an important predictor of cooperation in a non- coalitional group since non-coalition members are less likely to be encountered in iterative social interactions which serve as the basis behind the recuperation of costs expended in the cooperation when competing against other groups. This is supported by previous research in Conambo where warriors were only found to be reciprocated with social status by fellow coalition members but not by non-coalition members, even though rankings of men’s warriorship were not biased by coalitional affiliation (Patton, 2000).
Therefore, highly central individuals should only expend effort in cooperation when with coalition members. Additionally, if competition occurs between sub-coalitions of the same larger political coalition it would be unlikely that competitors from one coalition would be amenable to highly central competitors of the other coalition recuperating benefits through social interactions with each other. Considering these two points in unison highly central individuals could be expected to be more cooperative than others in
73 coalitional competition at the inter-group level. Though this prediction is only made for one of the PGG treatments the effect of centrality on cooperation will be explored among all the treatments. Also, since no predictions are derived that apply to any one specific centrality measure the several different candidate measures of centrality will all be explored simultaneously in a hierarchical regression model. Potential differences in the effect of these centrality measures are likely to reveal interesting aspects of how centrality specifically alters the cost-benefit structure of cooperation in the varying contexts tested here.
Hypothesis 6: Greater individual access to network capital via centrality increases individual cooperation in coalitional groups when competing at the intergroup level.
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CHAPTER 5
ANALYSIS AND RESULTS
The first two sections of this chapter relate to the visualization and exploration of coalitional-alliance structure and social networks in Conambo. While these graphical representations are not involved in explicit hypothesis testing they do represent values that are and provide an intuitive means for understanding the hidden social structure of
Conambo. The third section presents the ANOVA models that test hypotheses concerning differences in cooperative behavior stemming from the contextual manipulations of the
PGG treatments. The fourth section details the linear regression models of the individual- level predictors that best explain variation in offers within the individual PGG treatments.
Information-Sharing Network Analysis
A potential vector of social capital involves an individual’s position in their social network. Here I present data concerning the information-sharing network of Conambo.
This network includes every participating adult, (N = 44), since information-sharing is a relevant domain of men and women. In Figure 4 the red and blue nodes denote individuals nominally affiliated as politically Achuar or Sápara respectively. The triangles and circles represent nodes that are men and women respectively. Table 2 presents the specific values of the information network centrality variables.
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Figure 4. Information-sharing network diagram by coalition and sex.
Table 2. Descriptive Statistics of Information-Sharing Network Centrality Variables
Measures of network centrality Degree centrality Beta centrality Betweenness centrality Group N M SD M SD M SD Total 44 19.0 6.12 35.5 16.3 25.3 24.0 Men 22 20.5 6.26 38.6 16.6 27.3 24.5 Women 22 17.6 5.77 32.4 15.8 23.2 23.9 Achuar 22 16.9 6.92 27.4 13.2 24.4 28.0 Men 10 19.5 7.47 30.4 12.9 27.4 27.4 Women 12 14.8 5.88 24.9 13.6 21.8 29.5 Sápara 22 21.1 4.42 43.5 15.3 26.2 19.7 Men 12 21.3 5.26 45.4 16.7 27.3 23.1 Women 10 21.0 3.43 41.3 13.9 24.9 16.0
Coalitional-Alliance Structure
Anthropac and UCINet 6 were employed to create a multidimensional scaling
(MDS) visualization of the men’s and women’s coalitional-alliance structures. These
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MDS are generated using the aggregated strength scores derived from the coalitional pile- sorting task as detailed above. In sum, the programs automatically place individuals, represented here by the small red or blue points, closer or father away from each other depending upon the value of dyadic alliance strength scores as aggregated across all participant responses in the pile-sort task. Points closer together indicate individuals that are judged as possessing stronger alliances and more likely to ally with one another in a coalition against individuals in other coalitions. The red points indicate individuals that are politically affiliated with the Achuar coalition and the blue points represents individuals politically affiliated as Sápara
Figure 5. Multi-dimensional scaling of men’s alliance strength.
These MDS figures are useful in that they facilitate an intuitive understanding of the local coalitional-alliance structure of Conambo, for both the men and women. While it is apparent that the men and women of Conambo are both highly divided along political lines, it is also apparent that every individual is not equally divided from the other
77 political coalition; some men or women are perceived as being more allied than others with some members of the other coalition. Table 3 presents descriptive statistics of the pre-transformed alliance strength scores.
Figure 6. Multi-dimensional scaling of women’s alliance strength.
Table 3. Descriptive Statistics of Alliance Strength
Measures of alliance strength Total In-group Out-group Group M SD M SD M SD Male .36 .03 .56 .06 .18 .07 Female .36 .04 .55 .10 .21 .10 Achuar .37 .03 .50 .07 .21 .11 Male .34 .02 .54 .05 .18 .06 Female .39 .03 .47 .07 .23 .13 Sápara .36 .03 .60 .07 .18 .06 Male .38 .02 .57 .07 .18 .07 Female .33 .01 .64 .04 .19 .02
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In addition to using the alliance strength scores in the cells of a network matrix (a value matrix), cutoff points can be created and values above and below the cutoff can be assigned a value of one or zero to create a binary matrix. This allows for additional analyses to be done that cannot be performed on value matrices, such as betweenness centrality (Borgatti et al., 2013). When this is done the following network diagrams are produced and the descriptive statistics of the resulting network centrality variables are presented in Table 4.
Figure 7. Men’s alliance-network diagram.
Figure 8. Women’s alliance-network diagram.
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Table 4. Descriptive Statistics of Alliance-Network Centrality Variables
Measures of network centrality Eigenvector Betweenness Degree centrality centrality centrality Group N M SD M SD M SD Men 24 6.63 2.83 .116 .141 69.0 125.3 Women 24 7.17 2.62 .102 .112 66.7 93.8 Achuar Men 11 6.36 2.87 .0001 .0003 53.5 103.5 Women 13 6.38 2.96 .159 .127 97.0 115.4 Sápara Men 13 6.85 2.88 .214 .125 82.2 144.0 Women 11 8.09 1.87 .035 .006 30.9 40.7 Note: Women and men’s alliance networks are derived from sex-specific data tasks so centrality measures cannot be pooled across both sexes to derive the mean and standard deviation for each political faction.
Just as with the multidimensional scaling of the alliance strengths some individuals are more or less aligned across the coalitional divide. These types of cross- coalitional alliances have a considerable effect on individual betweenness scores as most members of a coalition are allied only with other coalition members. These relationships across the boundary and resulting betweenness are thought to imbue an individual as a social mediator between the two coalitions.
Hypothesis Testing
In this section the cooperation data as ascertained through the PGG is presented and two ANOVA models are performed: (a) a three-way mixed ANOVA to analyze any main effects, interactions, or significant differences between planned comparisons of the
PGG treatments; and (b) a three-way mixed ANOVA to ascertain if data are influenced by round order and not wholly by the context of the experimental conditions. Further,
80 hierarchical linear regression analyses are performed to model how individual-level predictor variables from the information-sharing and coalitional-alliance network influence contributions within each PGG treatment.
Cooperation in Coalitional and Competitive Contexts
A three-way 5 x 2 x 2 mixed ANOVA was performed. The levels of the within- subjects’ factor are defined as the five treatments of the PGG, and the between-subjects factors being coalitional affiliation (Achuar or Sápara) and sex (male or female). One
Achuar man was omitted from the analysis due to very poor understanding of the game, he had extreme difficulty in answering any of the comprehension questions even with numerous examples and re-explanations. Other than this one case all other participants are included in the model N = 48, with half belonging to each political coalition; Achuar n = 24, Sápara n = 24. Additionally, the number of participants were equal among the sexes as well; men n = 24, women n = 24. For the participants where the data exists
(N = 44) the average age was 37.3 years old (SD = 16.4) with an age range of 17 to 70 years old. Table 5 presents the mean offers as a percentage of the total endowment, and their standard deviations, across all five PGG treatments for each coalitional group and sex.
Analysis shows that the assumption of sphericity was violated to a small degree
χ2(9) = 17.16, p = .046, therefore the degrees of freedom are corrected using Huynh-Feldt estimates of sphericity (ε = .956). Levine’s test was also performed and indicates that the assumption of equality of variances between the levels of the PGG treatment factor held.
A main omnibus effect of PGG treatment was significant at the <.10 level (see Table 6).
However, none of the two-way interactions of PGG treatment with the between-subjects
81 factors were significant, as is also the case with the three-way interaction with both coalitional affiliation and sex.
Table 5. Descriptive Statistics of PGG Offers
Offers to the common-pool as fraction of endowment Treatment 1 Treatment 2 Treatment 3 Treatment 4 Treatment 5 Group M SD M SD M SD M SD M SD Total .47 .31 .44 .30 .52 .34 .53 .34 .50 .31 Male .39 .28 .41 .30 .50 .39 .49 .35 .44 .33 Female .56 .32 .48 .29 .54 .30 .58 .34 .57 .27 Achuar .50 .32 .50 .29 .63 .33 .59 .33 .57 .27 Male .43 .30 .51 .31 .64 .36 .57 .28 .52 .30 Female .56 .33 .49 .30 .62 .32 .61 .38 .62 .25 Sápara .45 .30 .39 .30 .41 .33 .48 .36 .44 .33 Male .35 .26 .32 .28 .38 .38 .42 .40 .37 .34 Female .56 .32 .47 .31 .46 .27 .55 .29 .52 .30
Neither were participants’ coalitional affiliation or sex found to be significant between-subjects main effects influencing PGG contributions. Additionally, their interaction was also not significant in effecting offers.
Table 6. Mixed ANOVA Omnibus Test of PGG Offers
SS DF MS F p η2 Main effects Treatment (A) 24.2 (3.8,168) 6.34 2.10 .087 .045 Political affiliation (B) 80.8 (1, 44) 80.8 2.08 .157 .045 Sex (C) 51.3 (1, 44) 51.3 1.32 .257 .029 Interaction effects A x B 17.9 (3.8,168) 4.67 1.55 .194 .034 A x C 13.9 (3.8,168) 3.64 1.20 .311 .027 A x B x C 2.66 (3.8,168) .697 .230 .914 .005 B x C 14.1 (1, 44) 14.1 .362 .550 .008 Note: p values are Huhn-Feldt corrected
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A bar graph of average offers in each treatment with offers pooled across coalitional affiliation and sex to graphically show the main effect of game treatment on offers (see
Figure 10).
0.6 0.5 0.4 0.3 0.2 0.1 0.47 0.44 0.52 0.53 0.5 AverageOffer as 0 T1 T2 T3 T4 T5 Percentageof Endoswment Public goods game treatments
Figure 9. Bar graph of average offers across PGG treatments.
One aspect of concern is whether merely the order that the participants played the game treatments had any effect on their offers. This could conceivably occur by participants offering a little more or less to the common-pool each successive round of the game, with progressively decreasing offers observed as a common pattern of contributions in iterated PGG rounds (Fehr & Gächter, 2002). Since the actual experimental conditions were randomized in relation to the round they were played I present the same mixed ANOVA model as above but define the round order as the within-subjects factor and statistically test for this influence on the data. If a significant main effect of round order is found, then the main effect of treatment on offers observed above is suspect.
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For this model both assumptions of sphericity and homogeneity of variances held.
The results of this statistical model provide assurance that it was the manipulated aspects of the experimental conditions; game groups being coalitional or not and the absence or presence of competition and against whom it took place, as being a casual factor impacting offers, with limited noise in the data being introduced from the inherent order of playing a sequence of five rounds of the PGG (see Table 7).
Table 7. Mixed ANOVA Omnibus Test of PGG Round Order
SS DF MS F p η2 Main effects PGG Rounds (A) 14.2 (4, 176) 3.54 1.18 .320 .026 Political affiliation (B) 80.8 (1, 44) 80.8 2.08 .157 .045 Sex (C) 51.3 (1, 44) 51.3 1.32 .257 .029 Interaction effects A x B 9.78 (4, 176) 2.45 .816 .516 .018 A x C 7.41 (4, 176) 1.85 .619 .650 .014 A x B x C 5.86 (4, 176) 1.47 .489 .744 .011 B x C 14.1 (1, 44) 14.1 .362 .550 .008
A contrast analysis was also conducted as part of the first mixed ANOVA model by specifying a priori comparisons between specific PGG treatments as hypothesized to isolate and test for significant effects of the manipulated aspects between conditions.
Since there are five comparisons being performed, which exceeds the norm of performing k-1 comparison, where k is the number of levels of the factor being compared, alpha is adjusted with a Bonferroni correction. Considering that there is only one contrast exceeding the (k-1) maximum, a corrected alpha level of .05 is produced to protect an original significance level of < .10. Therefore, an alpha level of < .025 represents an
84 original protected significance value of < .05 (Seltman, 2015). The other four comparisons are not corrected for considering that they are a priori contrasts derived on theoretical grounds (Keppel & Wickens, 2004). As well as the sample size being limited, given the ethnographic context, and that statistical power is therefore low, meaning additional corrections are not automatically necessary (Nakagawa, 2004). In addition, even though contrasts are non-orthogonal, since the correction to alpha is being made given the one contrast that exceeds the k -1 norm for the maximum number of allowed contrast and that power is lower than non-orthogonality can be ignored with relatively minor consequence (Seltman, 2015).
Hypothesis 1: In a context absent of between group competition, cooperation will be greater in coalitional groups than in the random game group
Prediction 1: Group cooperation, measured as the average contribution as a percentage of stake size, is significantly greater in T3 than in T1.
The mean offers of treatments one and three were contrasted to discern the effect of coalitional grouping on cooperation when competition against other groups is absent.
The is no within-subject main effect of on this contrast (see Table 8).
Table 8. Mixed ANOVA Contrast of Treatment One and Three
SS DF MS F p η2 Main effects PGG treatments (A) 10.3 (1, 44) 10.3 1.83 .184 .040 Political affiliation (B) 34.4 (1, 45) 34.4 6.23 .016 .122 Sex (C) 23.1 (1, 45) 23.1 4.18 .047 .085 Interaction effects B x C .308 (1, 44) .308 .055 .816 .001
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However, there was a difference in how the two political coalitions were effected by manipulating whether they played in a coalition (treatment 3) or not (treatment one).
Where the Achuar contributed 26% more to the common-pool when in the coalitional treatment than in non-coalitional groups.
0.8 0.7 0.6 0.5 Achuar 0.4 offers 0.3 Sápara Endowment 0.2 offers 0.1 0.50.45 0.63 0.41
AverageOffers as Percentage of 0 T1 T3 Public Goods Game Treatments
Figure 10. Bar graph of average offers in PGG treatments one and three by coalition.
In comparison, the Sápara contributed 9% less in the coalitional treatment than they did in the non-coalitional treatment. For a graphic representation of this coalitional difference refer to Figure 10. Additionally, there was a between-subject main effect of sex on offers, where men were found to offer 28% more in the coalitional treatment than in a mixed group while the women offered 4% less when in coalitional rather than mixed groups. There was no interaction of political affiliation and sex on the contrasted offers. For a graphic representation of this sex difference refer to Figure 11.
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0.8 0.7 0.6 0.5 Men's 0.4 offers 0.3 Women's Endowment 0.2 offers 0.1 0.390.56 0.5 0.54 0 AverageOffers as Percentage of T1 T3 Public Goods Game Treatments
Figure 11. Bar graph of average offers in PGG treatments one and three by sex.
Hypothesis 2: In a context of between group competition, cooperation will be greater in groups that are coalitionally organized rather than in groups that are randomly composed.
Prediction 2: Group cooperation, measured as average contribution as a percentage of stake size, is significantly greater in T4 than in T2.
The mean offers of treatments two and four were contrasted to discern the effect of coalitional grouping on cooperation when in competition with an out-group. This contrasting of treatments revealed a significant within-subject main effect on offers, with a 20% increase in offers when competing in a coalition than when competing in a non- coalitional group. There were no differences in the contrasted offers due to political affiliation, sex or any combination of interactions.
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Table 9. Mixed ANOVA Contrast of Treatment Two and Four
SS DF MS F p η2 Main effects PGG treatments (A) 36.9 (1, 44) 36.9 5.96 .019 .119 Political affiliation (B) .140 (1, 45) .140 .023 .880 .001 Sex (C) .473 (1, 45) .473 .078 .782 .002 Interaction effects B x C 1.86 (1, 44) 1.86 .301 .586 .007
Hypothesis 3: In a context of non-coalitional groups, cooperation will increase when in competition with another game group.
Prediction 3: Group cooperation, measured as average contribution as a percentage of stake size, is significantly greater in T2 than in T1.
There is no overall effect from the comparison of treatment one and two. There is a potential sex difference in the comparisons of offers between the treatments. Overall, women offered 14% less in treatment two than they did in treatment one, while men increased there offers by only 5% in treatment two. Though this difference is not significant given the correction to α that is required given the non-orthogonal nature of the contrasts.
Table 10. Mixed ANOVA Contrast of Treatment One and Two
SS DF MS F p η2 Main effects PGG treatments (A) 3.46 (1, 44) 3.46 .852 .361 .019 Political affiliation (B) 4.11 (1, 45) 4.11 1.02 .318 .022 Sex (C) 13.1 (1, 45) 13.1 3.25 .078 .067 Interaction effects B x C 3.46 (1, 44) 3.46 .852 .361 .019
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Hypothesis 4: In a context of coalitionally organized groups, the effect of coalitional competition in comparison to non-competing coalitional groups will significantly increase cooperation.
Prediction 4: Group cooperation, measured as average contribution as a percentage of stake size, is significantly greater in T4 and T5 than in T3.
Hypothesis 5: Offers will be significantly greater in coalitional groups competing across the main coalitional-political boundary than coalitional groups competing against other coalitional groups of the same political affiliation.
Prediction 5: Group cooperation, measured as average contribution as a percentage of stake size, is significantly greater in T5 than in T4.
There were no significant differences among the factors or their interactions between offers in a non-competitive coalitional context and competitive coalitional contexts. Additionally, there were no differences in offers due to the level at which competition occurred; intra-group and inter-group competition produced similar average offers to the common-pool.
Table 11. Mixed ANOVA Contrast of Treatment Three, Four, and Five
SS DF MS F p η2 Main effects PGG treatments (A) .005 (1, 44) .005 .000 .988 .000 Political affiliation (B) 41.9 (1, 45) 41.9 1.83 .183 .039 Sex (C) 26.4 (1, 45) 26.4 1.16 .288 .025 Interaction effects B x C .755 (1, 44) .755 .032 .858 .001
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Table 12. Mixed ANOVA Contrast of Treatment Four and Five
SS DF MS F p η2 Main effects PGG treatments (A) 4.31 (1, 44) 4.31 .943 .337 .021 Political affiliation (B) .210 (1, 45) .210 .047 .829 .001 Sex (C) 1.96 (1, 45) 1.96 .438 .512 .010 Interaction effects B x C .560 (1, 44) .560 .123 .728 .003
Network Centrality and Cooperation
To test predictions of how inter-individual differences differentially motivate cooperation a series of hierarchical linear regression models are conducted incorporating variables of network centrality and offers in the five PGG treatments. Additionally, the categorical predictors of sex and political affiliation are included in the models as well as age. This allows for possible sex or coalitional differences in offers across the different treatments to be assessed as well as controlling for possible age effects. For each analysis the first step or block in the regression model includes all the candidate centrality predictor variables. The second step includes the demographic variables such as age, sex, and political affiliation. First, models of information network centrality are fitted, then two separate models examine centrality measures in the men’s and women’s alliance networks. Regression results for the information-sharing network centrality predictors are presented in Table 13. These results show that an age effect was detected in the third, fourth, and fifth treatments with older individuals offering more than younger individuals. This offers support that older individuals are more coalitional than younger community members. The models of alliance network centrality are presented in tables
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14 and 15 and show that betweenness centrality negatively predicts offers in treatments two and three in the men’s network, while betweenness centrality positively predicts offers in treatment four in the women’s network.
Table 13. Hierarchical Regression of PGG Offers and Information-Network Centrality
Offers in each PGG treatment Treatment 1 Treatment 2 Treatment 3 Treatment 4 Treatment 5 BCa BCa BCa BCa BCa Variable B(SE) B(SE) B(SE) B(SE) B(SE) 95% CI 95% CI 95% CI 95% CI 95% CI Step 1 -.087 [-.263, -.089 [-.285, -.057 [-.345, -.065 [-.334, .016 [-.167, indegree (.090) .057] (.097) .108] (.117) .170] (.127) .190] (.100) .134] -.006 [-.082, -.025 [-.104, -.049 [-.131, -.050 [-.135, -.039 [-.119, beta (.042) .059] (.039) .054] (.047) .011] (.044) .021] (.043) .021] .014 [-.055, .030 [-.032, .040 [-.026, .050 [-.011, .011 [-.049, betweenness (.041) .142] (.030) .091] (.059) .244] (.039) .132] (.047) .237] Step 2 -.065 [-.358, -.074 [-.345, -.017 [-.397, -.090 [-.431, .076 [-.228, indegree (.134) .163] (.133) .198] (.167) .241] (.174) .185] (.151) .307] .013 [-.109, -.011 [-.131, -.009 [-.161, -.051 [-.184, .002 [-.120, beta (.071) .157] (.059) .109] (.084) .125] (.079) .078] (.069) .137]
-.007 [-.100, .014 [-.073, -.003 [-.131, .039 [-.060, -.027 [-.112, 91 betweenness (.052) .146] (.043) .102] (.072) .242] (.055) .174] (.054) .156] .055 [-.013, .034 [-.036, .072 [.008, .067 [.000, .055 [-.008, age (.040) .137] (.034) .103] (.031)* .128] (.032)* .143] (.033)† .127] -1.90 [-3.89, -.841 [-3.11, -.486 [-3.12, -1.08 [-3.57, -1.76 [-3.68, sex (1.15) .095] (1.11) 1.42] (1.31) 1.93] (1.28) 1.75] (1.10) -.040] -.039 [-3.36, .209 [-3.02, 1.40 [-3.04, -.459 [-4.30, .907 [-2.87, Political affiliation (1.80) 3.61] (1.59) 3.44] (2.27) 5.43] (2.14) 3.53] (1.87) 4.88] 2 R for step 1 .021 .035 .044 .057 .027 ΔR2 for step 2 .161 .049 .137 .101 .158 Note: † p < .1 * p < .05. Sex [Female = 0, Male = 1]; political affiliation [Sápara = 0, Achuar = 1]. Every model except the model for treatment two had violated either the assumption of normality of errors or homoscedacity, therefore the bootstrapped p values are reported, bootstrapping = 1000 samples.
Table 14. Hierarchical Regression of PGG Offers and Men’s Alliance-Network Centrality
Offers in each PGG treatment Treatment 1 Treatment 2 Treatment 3 Treatment 4 Treatment 5 BCa BCa BC BCa BCa Variable B(SE) 95% CI B(SE) 95% CI B(SE) 95% CI B(SE) 95% CI B(SE) 95% CI Step 1 -.127 [-.534, -.298 [-.787, -.683 [-1.21, -.133 [-.700, -.285 [-.881, indegree (.233) .237] (.258) .077] (.318)* -.155] (.339) .299] (.338) .192] -.007 [-.018, -.010 [-.019, -.015 [-.030, -.010 [-.021, -.006 [-.019, betweenness (.010) .000] (.005)* -.002] (.012)* -.001] (.006)† -.002] (.008) .004] Step 2 -.121 [-.607, -.265 [-.723, -.646 [-1.23, -.122 [-.821, -.271 [-.961, indegree (.283) .371] (.276) .124] (.406) .049] (.380) .423] (.372) .355] -.006 [-.024, -.008 [-.017, -.013 [-.029, -.008 [-.021, -.004 [-.016, betweenness (.012) .004] (.006)† .000] (.009)† .003] (.009) .002] (.010) .004] .045 [-.062, .029 [-.055, .062 [-.054, .078 [-.033, .068 [-.012, age (.048) .142] (.041) .109] (.047) .178] (.046) .175] (.049) .150] 92 .267 [-2.46, 1.54 [-1.17, 1.73 [-.901, .504 [-2.30, .663 [-2.08, political affiliation (1.40) 3.10] (1.29) 3.92] (1.53) 4.12] (1.36) 3.41] (1.43) 3.96]
2 R for step 1 .084 .167 .291* .116 .064 ΔR2 for step 2 .077 .111 .144 .151 .147
Note: † p < .1 * p < .05. Political affiliation [Sápara = 0, Achuar = 1]. Eigenvector centrality was too multicollinear with political affiliation (VIF = 10.94) so it was removed from the models. Every model had violated either the assumption of normality of errors or homoscedacity, therefore the bootstrapped p values are reported, results are based on 1000 bootstrap samples.
Table 15. Hierarchical Regression of PGG Offers and Women’s Alliance-Network Centrality
Offers in each PGG treatment Treatment 1 Treatment 2 Treatment 3 Treatment 4 Treatment 5 BCa BCa BCa BCa BCa Variable B(SE) 95% CI B(SE) 95% CI B(SE) 95% CI B(SE) 95% CI B(SE) 95% CI Step 1 -.116 [-.771, -.167 [-.880, -.313 [-.932, -.171 [-.881, -.277 [-.914, indegree (.311) .540] (.352) .282] (.288) .120] (.368) .392] (.297) .165] -2.67 [-18.0, -2.29 [-14.3, 8.83 [-6.96, 4.26 [-21.3, -1.74 [-17.0, eigenvector (7.29) 12.7] (6.78) 8.50] (7.73) 22.6] (25.1) 11.2] (5.49) 9.78] -.006 [-.022, -.001 [-.015, -.006 [-.020, .017 [.006, .002 [-.008, betweenness (.008) .011] (.008) .009] (.008) .009] (.008)* .025] (.008) .015] Step 2 -.191 [-1.52, -.149 [-1.58, -.078 [-1.20, -.582 [-1.83, -.290 [-1.52, indegree (.624) 1.14] (.761) 1.18] (.611) .842] (.685) .553] (.659) .719] -.846 [-35.7, -2.94 [-41.6, 1.83 [-32.7, 6.12 [-27.4, 1.87 [-33.9,
eigenvector 93 (16.3) 34.0] (21.1) 29.7] (18.3) 36.4] (35.1) 40.1] (16.5) 34.1] -.004 [-.029, -.001 [-.027, -.008 [-.031, .025 [-.001, .003 [-.016, betweenness (.012) .021] (.016) .021] (.014) .016] (.016)† .053] (.015) .035] .018 [-.090, .012 [-.140, .046 [-.101, .066 [-.053, .037 [-.065, age (.051) .126] (.057) .180] (.053) .158] (.051) .166] (.046) .136] -.550 [-8.91, .138 [-12.5, 1.76 [-7.72, -3.02 [-10.6, -.077 [-8.08, political affiliation (3.92) 7.81] (5.07) 10.6] (4.16) 9.08] (4.16) 4.00] (4.25) 6.80]
2 R for step 1 .063 .045 .124 .256 .105 ΔR2 for step 2 .009 .004 .069 .107 .044
Note: † p < .1 * p < .05. Political affiliation [Sápara = 0, Achuar = 1]. Every model except the model for treatment two had violated either the assumption of
normality of errors or homoscedacity, therefore the bootstrapped p values are reported, bootstrapping = 1000 sample
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CHAPTER 6
DISCUSSION AND CONCLUSION
Discussion
Cooperation in Coalitional and Competitive Contexts
Several unequivocal a well as merely suggestive points result from the analyses performed. The first is that the context of cooperation, both in regard to group organization and the context of competition, were causal influences on cooperative offers. With the overall greatest and only significant effect evoked in the manipulation of group organization, from non-coalitional to coalitional groups, when in a competitive context (i.e., T2 and T4). This could be the only main effect detected among the contrasts for a combination of reasons. Competition is usually seen as a motivating factor for enhancing cooperative effort. However, in prior research which has detected a competition effect on cooperation the participants were pulled from a WEIRD sample, where participants are often university undergraduate students from western, educated, industrialized, rich, and democratic societies (Burton-Chellew et al., 2010; Egas et al.,
2013; Tan & Bolle, 2007). It is likely that the coalitional dynamics and considerations that are an aspect of day to day life in Conambo are not salient factors of these students’ everyday experience. This could explain why student participants often increase cooperation when competing in the absence of enduring coalitional groups, which was not found in Conambo when contrasting treatments one and two, the equivalent of the
95 comparison of non-competitive and competitive game conditions in prior research. In
Conambo the competitive but non-coalitional context (treatment two) elicited less cooperation than the non-coalitional non-competitive context (treatment one) though the overall difference between them is not large. Also, women were found to contribute less in the competitive context though not quite to a degree that reached statistical significance. This supports that competition possibly presents individuals with a disincentive to cooperate when not with coalitional partners and it is only when participants are placed in a coalitional group when competing that greater cooperative behavior is triggered.
Another conclusive result was in the detected coalitional difference in the effect of coalitional group organization in non-competitive contexts. The analysis revealed that offers made by Achuar participants increased by 26% when playing the PGG with a coalitional group in reference to a mixed group, both treatments absent of any competition. In contrast, the offers made by Sápara participants decreased by 9% on average in the coalitional group in reference to the first treatment. This suggests that there is a coalitional difference between the Achuar and Sápara in the expected benefits of cooperating with their fellow coalition members. Prior research and data support that the
Achuar are the more cohesive and cooperative coalition in Conambo. Previously the
Achuar of Conambo exhibited greater cooperative offers in an ultimatum game than the
Sápara, with the average Achuar offer being 74.4% greater than the average Sápara offer
(Patton, 2004). Also, Achuar men have exhibited a significant positive relationship between their social status and giving meat to a greater number of households, while this
96 relationships was not found among Sápara men (Patton, 2004), which further supports that prosociality is a pursued strategy among the Achuar but not the Sápara.
Another between-subjects effect was exhibited by a sex difference in cooperating with in-group coalitional members. Specifically, a sex difference in offers was revealed by contrasting treatments one and three. Male participants increased offers on average by
28%, while female participants made 4% lower offers on average in the coalitional treatment in comparison to the non-coalitional treatment. This would seem to support that non-kinship based alliances can be important in motivating coalitional cooperation, considering that post-marital residence is generally matrilocal and women are on average related to more individuals and to a greater extent than men are. It has long been noted in the ethnographic descriptions of this region that affinal alliances among men are highly important considering norms of sons-in-law giving political and coalitional support to their fathers-in-law as a form of bride service (Harner, 1984). These data support this general observation that kinship is not always the most universal and effective type of social bond in motivating cooperation within a coalition. Kinship relations therefore seem to allow for more flexibility in the specific confluence of coalitional membership and group cooperation, where the constraints of alliance relationships among men, especially among sons-in-law and fathers-in-law allows for less flexibility in deviation away from cooperating with the coalitional in-group.
Interestingly, there was no observed difference in offers between the treatments with coalitional groups sans competition and coalitional groups with competition
(treatment three compared to treatments four and five), or in comparison of coalitional groups at the different levels of competition (treatment four and five). It is curious that
97 there is no enhanced cooperation as an effect of varying competition in coalitional groups. However, this might be understandable considering the ethnographic literature on the flexibility of social identity and the active role and flexible nature of segmental politics and conflict among these particular societies and tribal societies in general
(Boehm, 1992, 1999; Gill, 1940; Harner, 1984). Additionally, these results run contrary to the male warrior hypothesis, which predicts that males are more cooperative with in- group members in the context of an out-group threat or competition (Van Vugt, 2009), since there was no sex difference in cooperation in the coalitional groups by varying competition (treatments three compared to four and five).
Cooperation and Centrality
Several interesting results emerged from the regression analyses. One robust effect was the ability of age to predict greater offers in the coalitional treatments (i.e., treatments three, four, and five) in the regression models of information-network centrality. Older participants cooperated more than younger participants in coalitional groups. It is curious why this would be found. Age is a rough proxy for experience and one salient aspect of regional history is the endemic raiding and warfare that characterized previous Achuar-Achuar violence and conflict more generally. As mentioned in chapter three, past informants had indeed called this period of intense coalitional aggression as “the times when we were ending” and reflects the period from which the multiple calculated homicide rates exhibited that violent conflict accounted for half of all male deaths.
It has also been previously suggested from research among older research participants from a WEIRD sample that they are less able to actively inhibit inherit out-
98 group biases in comparison to younger participants (Radvansky, Copeland, & von
Hippel, 2010). Additionally, there are reasons to believe that the younger individuals of
Conambo are actively trying to overcome past coalitional divisions. In limited instances, younger participants would fail to conform to the instructions of the pile-sort task and say something to the effect of “we used to be divided here, but it isn’t like that anymore” and they would indicate that the initial and singularly large group of photo IDs couldn’t be divided by a hypothetical conflict. Though beyond this age effect no measure of centrality in the information network adequately predicts greater offers in any of the PGG treatments. This could indicate that the ability of highly central individuals to differentially manage and manipulate information is not as valuable or does not translate as well into tangible benefits as they do in the coalitional-alliance network. This is supported by the comparison of density measures of the men’s and women’s alliance networks and the information-sharing network. Density assesses the probability that a tie exists between any pair of randomly chosen nodes in a network and operationalizes the degree of cohesion a network exhibits (Borgatti et al., 2013). The coalition-alliance networks are similarly dense for both the men and women, .253 and .217 respectively, while the information network produces a density measure of .442. The greater density of the information network lends support to the notion that information is less monopolizable and diffuse through the network as individuals can access valuable information through a number of different connections. Though this runs counter to the description of the importance of manipulating information provided by Descola it is not reflected in the data or the analysis conducted here (1996).
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Centrality measures derived from the men’s alliance network are predictive of offers in some PGG treatments. Specifically, betweenness centrality predicts lower offers made in the second and third treatments in both blocks of the hierarchical regression, so this effect remains once age and political affiliation are included in the model as predictors. Additionally, betweenness also predicts lower offers in the fourth treatment but this effect isn’t present in the second step of the model. Likewise, degree centrality was found to predict lower offers in the third treatment but only in the first step of the model, the effect disappears once age and political affiliation are added. Only one measure of centrality in the women’s alliance network was found to predict offers. In treatment four betweenness centrality predicted greater offers in both steps of the regression model. These results support that betweenness centrality derived from the network of alliance relationships is the most effective centrality measure in predicting offers but that it also has a variable affect across the treatments and across sexes, including in which direction it predicts offers.
Is betweenness centrality derived from alliance network structure differently in men and women? If it is, could it be responsible for the differential direction in which betweenness centrality is predicting offers? I argue that there is a difference in how centrality is derived from the men’s and women’s alliance network structure and this differentially affects confidence and ability in controlling enduring political support for individual political ends. Where centrality in the women’s alliance network reflects positions of greater stability in political control and therefore individual value, while betweenness centrality in the men’s alliance network is derived from positions of coalitional and political instability.
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Highly between women were more cooperative when competing in a coalition against another coalition of the same political affiliation. It is clear from the network diagram below, that women’s high betweenness centrality is partly derived from multiple alliances across the major coalitional divide but also significantly from linking separate sub-coalitions within one of the major coalitions. Figure 12 indicates that the most central individuals are disproportionately Achuar women. In Figure 13 a scatterplot shows the relationship between treatment four offers and betweenness centrality and is grouped by coalitional affiliation. It provides support that the centrally positioned Achuar are driving the relationship between centrality and offers an intra-coalitional competition.
Figure 12. Women’s alliance-network: node size scaled by betweenness scores.
Separate trend lines are included for the Achuar and Sápara and additionally show that this relationship is not operating among Sápara women. This being the case, why are women who derive their betweenness from their alliances across the main coalitional divide as well as from key alliances connecting Achuar sub-coalitions cooperating more when competing against another Achuar coalition in treatment four?
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1
0.8 Achuar 0.6 Sápara 0.4
Endowment Linear 0.2 (Achuar)
Offersas Percentageof Linear 0 (Sápara) 0 100 200 300 400 Betweenness Centrality
Figure 13. Scatterplot of women’s betweenness centrality and treatment four offers by coalition.
An explanation requires understanding that these alliance relationships are informal obligations of political support that are contractual in nature, but that are also shifting. Betweenness centrality in the alliance network can be conceptualized as monopolization of or gatekeeping ability in accessing political support and more specifically in terms of cultivating political consensus and mediating political conflict
(Bowser & Patton, 2010). Considering this, gatekeepers of political support become valuable individuals to give and receive political support from. They can deliver or transfer the support of their allies, whom have obligations to support them, to ends desired by others. These gatekeepers can utilize this leverage in manipulating greater support or acquisition of leadership potential and social status in return (Bowser &
Patton, 2010). However, an important consideration is that alliances aren’t static. If central individuals fail to deliver adequate benefits through political support to their circumscribed segment of the alliance network, then their allies may dissolve these
102 alliance relationships and develop obligations of political support with non-mutual allies.
Thereby, reducing the gatekeepers’ confidence in controlling and accruing benefits in the future from gatekeeping and leveraging this political capital. If this is the case, then it is likely individually beneficial to pay costs that benefit coalitional allies if it preserves this gatekeeping ability.
Men who occupy positions of greater betweenness in the alliance network are less cooperative in the non-competitive coalitional context (T3) and in the competitive non- coalitional context (T2).
Figure 14. Men’s alliance-network: node size scaled by betweenness scores.
In the network diagram (Figure 14) high betweenness centrality appears to be wholly derived from a chain of single alliances connecting the major Achuar and Sápara coalitions. However, these central positions in the men’s alliance network, unlike central positions in the women’s alliance network, are positions of political instability. Being between the two major coalitions in this way is not a favorable position in which an individual can leverage their political access to the other coalition in support of their
103 allies on the other side of the divide. Especially considering that the men were found to be incentivized to cooperate more when in coalitional groups than when in mixed groups.
Which is consistent with men’s centrality being politically unstable across the coalitional divide and with women deriving political centrality and therefore political leverage at the intra-coalitional level. Additionally, low offers by central men in treatment three can be explained if these alliances that connect individuals to outgroup coalitions are meaningful and that the presence of these alliances lead to generally weaker alliances to other individuals of the same major coalition (Achuar or Sápara). In other words, if an individual is allied across the coalitional divide they may not have as strong alliances to all members of their nominal political coalition or identify as strongly with their nominal political affiliation and therefore aren’t increasing offers when playing a game treatment with “in-group” coalition members.
These interpretations of the effects of betweenness centrality on group cooperation rely on an assumption that individuals are biased towards cognitively envisioning being anonymously placed in game groups with more closely allied individuals than with more socially distant individuals. If they were indeed biased in this way, then the differential basis and political stability of betweenness centrality in the men’s and women’s alliance networks supports why betweenness can predict both greater and lesser offers in some PGG treatments. Additionally, the differential function of male and female alliances is also surely one factor that affects the difference seen in the relationship of betweenness centrality and cooperation. As it has been noted, female alliances function to ultimately build political consensus and mediating or resolving potential conflict (Bowser & Patton, 2010). While male alliance relationships constitute
104 contracts of mutual defense or support potentially in contexts of violence and conflict
(Patton, 1996).
Additionally, it is critical to note dynamics of variable social group identification and categorization. This could be a pertinent aspect of why there is no effect of competition on cooperation in coalitional groups and why there is a sex difference in betweenness on coalitional competition. As Wiessner (2016) notes, the salient in-group out-group distinction is a universal feature relevant to human aggression. The data presented here undoubtedly support this proposition, in that individuals are only investing in costly cooperation against any other type of outgroup when in the company of fellow in-group members. However, while the consideration of the in-group and out-group are constant features of aggression the line that defines these relative social groups is flexible. As Wrangham (1999) aptly summarizes: “as a result of cultural beliefs or social pressure, individuals can either broaden or contract their concept of where an in- group/out-group boundary falls, or of how important it is.” (p. 24). In regards to the context of this research, network centrality seems to be an important consideration in how certain individuals draw this line and perceive the benefits of cooperating with coalitional members.
Men connected by alliances to individuals across a coalitional divide may not perceive it that way and when in the experimental context of the game don’t cooperate with the preconceived defining of the coalitional in-group. Additionally, the women in central network positions between sub-coalitions may define the relevant coalitional boundaries within the larger in-group political coalition, thus motivating their increased cooperation against competing groups of the same ethnic coalition. Indeed, further
105 inspection of pertinent ethnographic materials reveals this dynamic of fluctuating aggregation of social groupings in service of competing against similarly aggregated social groups (Gill, 1940; Harner, 1984).
Conclusion
Here, I sought to discern the relevant contextual features that motivate greater in- group cooperation, with respect to group organization and competition. Furthermore, centrality of social network position was experimentally tested as an important aspect in which individuals differ that promotes cooperation in competitive contexts.
The ANOVA treatment contrasts support that coalitional group organization (i.e., cooperating with a persisting group with which individuals socially identify), competition, and the combination of these elements were important in increasing cooperation in a relevant ethnographic context for studying coalitional aggression.
Additionally, interesting sex and coalitional differences where observed in how individuals cooperated and in which contexts. These results broadly agree with prior research and lend more robusticity that cooperation in service of competing against another collective was a pertinent aspect of the social environment of human evolution and that enhanced cooperation can be triggered given minimal but relevant cues.
At first glance the results from the men’s alliance network do not offer much empirical support for theory that posits individual differences in social support effects cooperation in intergroup competition, at least in regards to differences in network centrality. However, this could stem from betweenness centrality deviating away from key assumptions of the tested theory. Centrality in the men’s alliance network isn’t derived from variation in network position representing in-group heterogeneity in
106 alliances relationships. This indicates that these positions are circumstances of structural instability and political risk. However, betweenness centrality in the women’s alliance network is derived from structurally advantages positions in the realm of brokering or leveraging political capital within and between the two major coalitional factions in
Conambo. This more clearly connects with the key assumptions of the relevant theory and produces tentative support and is largely consistent with what theory expects.
However, unlike as is described by Gavrilets and Fortunato, the group with which betweenness predicted greater cooperation in competing against was of the same larger political coalition of Conambo, which only marginally agrees with theory in that it is technically an out-group (i.e., a separate group being competed against). It is relevant to note that ethnography of this region, and Amazonia in general, observe considerable conflict between different communities of the same ethnolinguistic group and tribe
(Walker & Bailey, 2013). Weighing these considerations, I argue that this result from the women’s alliance network does support the theory though the same effect wasn’t seen in the context of competing against a group across the main coalitional divide.
It should obviously be noted that theory of inter-individual differences motivating cooperation posits that many domains in which individuals possess differential abilities, endowments, and motivation could be relevant in enhancing collective action. Many potential aspects in which individuals differ and is pertinent to favoring cooperation are not tested here. Though, the limited support and acknowledged reservations mentioned here suggest that continued research and testing of predictions derived from this theory are justified and provide a possibly productive theoretical mechanism in explaining cooperation in inter-group competition.
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The research presented here could be expanded in several ways to further enhance our knowledge on the subjects discussed. First, logistical considerations concerning the conducting of the PGG could be incorporated. Ideally, the playing of the treatments could be spread out over time or have some sort of distraction task between them. There was a possible concern with the rapid nature with which each participant played the treatments, but it seems clear through the analyses that the context of the treatments and sufficient randomization of order with which treatments were played limited any influence of round order on the ratcheting up or down of offers over the sequence of game treatments.
However, it should be noted that if treatments are spread out this significantly increases the risk that participants could divulge information about the game with participants who have yet to play, which constitutes a grave methodological concern.
It would be interesting to incorporate methods of other research which had much greater stakes for losing or winning into the PGG conditions. Such as having a losing group forfeit any possible payoffs after competing with a more cooperative group. This might more align game structure with ethnographic scenarios where failure to adequately account for inter-group conflict results in significant fitness costs. Such as, being injured or killed, or having a family member, sister, daughter, or wife captured in a raid. A logical expansion of this thesis would be to conduct comparable PGGs in other communities and have competition take place between game groups between different communities while varying the ethnic identity of those groups. Doing so would facilitate understanding of how proximity and ethno-linguistic group membership interact in coalitional competition. Is cooperation increased by playing against a group of similar ethnic group members in a different community rather than a similar group from the same
108 community? And conversely is cooperation increased by playing against a group of non- coalitional group members in a different community than a similar group from the same community? This last question is particularly germane to the context of Conambo considering that out-group coalitional members are technically members of the same community where non-negligible interactions occur even though the community is coalitionally bifurcated.
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APPENDIX A
PUBLIC GOODS GAME ENGLISH PROTOCOL
“Thank you for attending this study. For the time you are taking to be here today we will give you $1. This money is yours to keep and will be given to you in a few days when we go to visit you in your house. Please remember that if at any time you feel you do not want to participate in this study you are free to leave whether we have started or not and you will still receive $1 for being here today. Participation in this study involves no foreseeable risk to anyone who wished to take part. Would you like to participate?” “We are going to play a game. Please pay this game seriously because you can earn more money in this game. The money earned in this game, along with your $1, will be given to you in a few days when we come to visit you in your house. For this study, you need to remember several points. The first is that the game we are about to play is different from other games played previously in Conambo. For this game, you will be playing in a group with three other people. You will not be able to know who the other three people in your group are and the other people in your group will not be able to know who you are. You and the other players will only know if the other people in their group live up or down river. The decisions you make during the game will be completely unknown to the other group members. Only I will know what you contribute and what money you earn in the game. I will not tell any other people what any person decided to do in the game. The second point is that all decisions you will make in the game will be for real money. The third point is that the money you may earn in the game does not belong to me. It has been given to me by the school to conduct this study. It does not matter to the school whether this money is spent or not. The fourth point is that once you are done playing the game please do not discuss the game with anyone until after everyone has finished playing the game. This is very important. If you disobey this rule you can spoil the game for other people and they will not be able to play the game. Everyone will be done playing by Tuesday.” “I will now tell you the rules of this game. It is important that you listen carefully and understand these rules, because only those people who understand the rules will be able to play. You will be playing the game multiple times, each time you will be placed in a group with three other people and each time you play the game you will play with three completely different people. Each group will be given a group pot. Each person in the group will receive an individual endowment of ten quarters. These ten quarters belong to you only. You are able to deposit as much or as little of your ten quarters into the group pot as you wish. This means that you have the option to deposit 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, or all 10 of your quarters into the group pot. The money that you do not deposit into the group pot is yours to keep and take home. Each person you are playing with will be deciding how much of their ten quarters, they want to put into the group pot as well.
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After each group member has made their decision I will count how much money has been placed into the group pot and I will double the amount of money in the group pot. Once the group pot has been doubled it will be divided equally and given to you and the three- other people in your group. Hence, after the game you will receive the amount of money that you did not deposit into the group pot, plus an equal share of double the amount in the group pot. Therefore, in this game you will decide how much of your ten quarters you want to keep for yourself and how much you want to put into the group pot. Remember that everyone in your group will make the decision independently and in private so that none of the other group members can ever know the decisions of the others. Also, you will be playing a version of the game where your group will be competing with another group of players for an extra reward of money. The group with the greater amount of money in the group pot will be the winner, and the individuals in the winning group will each receive another $1. Now I will give you some examples so that you understand the game properly.” Example 1: “If all of the players in a group deposit their total endowment of ten quarters into the group pot, then the group pot will contain 40 quarters. I will then double the group pot so that it contains 80 quarters. Each person will then receive an equal share of the 80 quarters which is 20 quarters for each person.” Example 2: “If all the players in a group deposit nothing into the group pot and keep the ten quarters for themselves the group pot will be zero. Since there is no money in the group pot, no one will get a share of the group pot but each person will still receive their ten quarters for themselves.” Example 3: “If one group player does not put any money into the group pot and the three other people each put all of their ten quarters into the group pot, then the group pot will contain 30 quarters. Remember, that I will double the group pot, so it would then contain 60 quarters. Each person, even the player who put in nothing will get an equal share of the 60 quarters. Each share will be 15 quarters. However, since the player who put in nothing keeps their 10 quarters they will receive 25 quarters while the three other people each receive 15 quarters.” Example 4: “If one person in a group puts all 10 quarters into the group pot and the three other members put nothing and each keep their 10 quarters then the group pot will only contain ten quarters. I will double the group pot so that it contains 20 quarters. Each player will then receive an equal share which is five quarters. This means that the player who put all ten of their quarters into the group pot will only receive five quarters while the three other players who put in nothing will still receive five quarters plus the ten quarters they each kept for themselves, so in total they receive 15 quarters.” Example 5: “Now I will explain an example of the group competition game. In group A every person puts all ten quarters into their group pot so that it contains 40 quarters and 80 quarters once it has been doubled, like in the previous examples. They are competing with group B where each player puts in nothing into their group pot, like in example 2. Since group A had more money in their group pot they will win and receive an extra reward of money.” “There are several important points to remember. If all group members put some money into the group pot they will earn more money that if no one puts any money into the group pot.
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If most group members put some money into the group pot but a few people do not, then the people who did not will earn more money than the players who did put some money into the group pot. If most group members do not deposit any money into the group pot but a few people do put some money into the group pot, then the few people who did will earn less money than those in all the other examples given so far. If two groups are competing, then the group with more money out into their group pot will win the extra award of money.” “Now I will ask you some questions to check whether you have understood the rules of the game.” Question 1: “What decision must each person in a group make about their ten quarters?” Answer: how much to put into the group pot. Question 2: “Once each person has decided how much money they want to put into the group pot what will I do?” Answer: double it. Question 3: “If two groups are competing how is the winner determined?” Answer: the group with more money in their group pot. “Now you will play the game. Remember that there is no right or wrong answers in this game. Here are your ten quarters. You must decide how many of these ten quarters you want to put into your group pot and how much to keep for yourself. Remember you can put nothing in the group pot if you wish or you can put in any amount up to all of the ten quarters.” “In this game the other players in your group include …” Treatment 1: “One other ‘in-group’ person and two ‘out-group’ people. There is no competition with any other group.” Treatment 2: “One other ‘in-group’ person and two ‘out-group’ people. Also, there is competition against a similar group.” Treatment 3: “Three other ‘in-group’ people. There is no competition with any other group.” Treatment 4: “Three other ‘in-group’ people. Also, there is competition against another group whose members are all ‘in-group’ people.” Treatment 5: “Three other ‘in-group’ people. Also, there is competition against another group whose members are all ‘out-group’ people.” “Please put the amount you want to put into the group pot across the line and keep the rest on this side. Thank you” “Now we are going to play again. The rules are exactly the same. The only difference is that in this game the other players in your group include …” After all treatments are played: “Thank you. You are now done play this game. Remember that some people have not played yet and you cannot talk about the game with anyone until after Tuesday. If you do, then we cannot finish the study and other people won’t be allowed to play. Thank you.”
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APPENDIX B
PUBLIC GOODS GAME SPANISH PROTOCOL
“Gracias por participar en este estudio. Por el tiempo que vas a estar aqui te daremos 1 $. Este dinero es tuyo y te lo entregaremos cuando te vistemos en tu casa. Por favor recuerda si en cualquier momento sientes que ya no quieres participar, puedes retirarte sin importer que ya hayamos empezado el estudio. En caso de que desees retirarte aun asi reciviras el 1 $ por participar. No existe ningun riesgo si participas. Te gustaria participar?” “Vamos a jugar un juego. Por favor es importate que jueges enserio este juego por que puedes ganar mas dinero. Tanto el dinero que ganes aqui como el dinero por participar se te entregara cuando te vistemos en tu casa. Para este estudio es importante decirte algunas cosas. La primera es que el juejo que vas a jugar es distinto de otros juegos que se han jugado antes en Conambo. Para este juego vas a jugar con otras tres personas. Tu no vas a saber quienes son estas personas y ellas tampoco van a saber quien eres. Tu y los otros jugadores sabran si son Achuar o Sápara. Las decisions que tomes en este juego son completamente desconocidas por los otros miembros del grupo. Solo yo sabre cuanto diste, y cuanto dinero ganaste en este juego. No le dire a nadie cuales fueron las decisiones que cada persona del grupo tomo.” “El Segundo punto es que todas las deciciones que tomes en este jeugo seran por dinero de verdad. El tercer punto es que el dinero que ganes no es mi dinero. Me lo dio la Universidad para realizer este estudio. A la Universidad no le importa si el dinero se gasta o no. El cuarto punto es que despues de jugar el juego te pedimos que por favor no hables con nadie sobre el juego. Solo puedes hablar despues de que todos hayan terminado de jugar este juego. Esto es mu importante. Si hablas con alguien, esto arruinara el juego y las personas que quisieran jugar ya no podran jugar. Todos terminaran de jugar el dia Martes.” “Ahora te dire las reglas del juego. Es importante que prestes atencion y entiendas las reglas del juego. Solo las personas que entiendan las reglas podran jugar. Vas a jugar el juego varias veces. Cada vez vas a estar en un grupo con tres personas. Y cada vez que el juego empieze de Nuevo vas a jugar con tres personas diferentes al juego anterior. “El grupo en el que vas a estar con las otras tres personas tiene un pozo comun. A cada persona en el grupo se le dara 10 monedas de 25 centavos. Estas 10 monedas de 25 centavos son solo tuyos. Tu puedes dar al pozo comun cualquier cantidad del dinero que se te ha dado. Esto significa que tu puedes dar nada, 1 moneda ,2,3,4,5,6,7,8,9 o las 10 monedas de 25 centavos. El dinero que no pongas en el pozo comun es tuyo y te lo daremos cuando te visitemos en tu casa.” “Cada una de las personas que estas jugando tambien decidira que cantidad de las 10 monedas de 25 centavos dara al pozo comun. Despues de que todas las personas
113 hayan decidido cuanto dar al pozo comun, yo voy a contar todo lo que las personas de tu grupo incluyendote a ti, pusieron en el pozo comun. Despues de contar yo voy a duplicar esa cantidad y lo dividire de manera igual y se los dare de vuelta a ti y a las otras personas del grupo. Entonces al final del juego tu tendras la cantidad que decidiste no dar al pozo comun, mas una porcion del pozo comun divida de manera igual entre todos los jugadores de tu grupo. Entonces en este juego tu decidiras cuanto de tu 10 monedas de 25 centavos quieres quedarte y cuants quiers dar al pozo comun. Recuerda todas las decisiones que tomes son independientes y nadie mas sabra que es lo que tu decidas. Te dare unos ejemplos.” Ejemplo 1: “Si todos los jugadores del grupo dan todas sus 10 monedas de 25 centavos al pozo comun. Entonces el pozo comun tendra 40 monedas de 25 centavos. 10 por cada jugador. Yo duplicare esa cantidad. Entonces en vez de 40 monedas Habra 80 monedas de 25 centavos en el pozo comun. Luego yo dividire las 80 monedas entre los cuatro jugdores. Eso significa que cada persona en el grupo recivira 20 monedas de 25 centavos.” Ejemplo 2: “Si todos los jugadores en el grupo deciden no poner nada en el pozo comun. Entonces el pozo comun tendra nada. Como no hay dinero en el pozo comun yo no puedo duplicarlo y nadie recive nada del pozo comun pero cada jugador se queda con sus 10 monedas de 25 centavos.” Ejemplo 3: “Si uno de los jugadores no pone nada en el pozo comun y las otras tres personas ponen cada una sus 10 monedas de 25 centavos, el pozo comun tendra entonces 30 monedas. Yo duplicare esa cantindad. El pozo comun tendra entonces 60 monedas. Yo repartire las 60 monedas entre los 4 jugadores, dandoles 15 mondas a cada uno. Como uno de los cuatro jugadores no puso nada, el se queda con sus 10 monedas y recive ademas las 15 monedas del pozo comun. Eso significa que el jugador que no puso nada tiene 25 monedas mientras que los que si pusieron tienen 15 monedas cada uno.” Ejemplo 4: “Si una persona en el grupo pone sus 10 monedas en el pozo comun, y las otras tres personas deciden no poner ninguna de las 10 monedas que se les han dado. El pozo comun tendra las 10 monedas de la persona que si puso. Yo duplicare esa cantidad. Ahora el pozo comun tendra 20 monedas. Despues yo repartire las 20 monedas entre los 4 jugadores dandoles 5 monedas a cada uno. El jugador que puso todo recivira entonces 5 monedas mientras que los que pusieron nada tendran sus 10 monedas cada uno mas las 5 monedas del pozo comun dando en total 15 monedas para los jugadores que no pusieron nada.” “Tambien vamos a jugar un juego parecido al anterior. En que cada grupo de 4 jugadores va a competir con otro grupo de 4 personas por mas dinero. El grupo con mayor cantidad de dinero gana. Y las personas del grupo gandor reciviran un dolar mas por estar en el grupo ganador. Ahora te voy a explicar con un ejemplo el juego de competecia. En el grupo 1 cada una de las 4 personas pones las 10 monedas de 25 centavos en el pozo comun. Entonces en el pozo comun hay 40 monedas de 25 centavos Yo duplicare esa cantidad dando 80 monedas. Igual que en el ejemplo anterior. El grupo 1 esta compietiendo con el grupo 2. En el grupo 2 nadie pone nada. Como el grupo 1 puso mas monedas en el pozo comun. El grupo 1 gana. Cada persona entonces del grupo 1 recivira un dolar extra.” “Hay algunos puntos que son importantes que recuerdes.”
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“Primero. Si todas las personas del grupo ponen dinero en el pozo comun,las personas del grupo ganaran mas dinero que si nadie pone nada de dinero en el pozo comun.” “Segundo. Si la gran mayoria de personas del grupo ponen dinero en el pozo comun, pero algunos no, entonces los que no puiseron nada tendran mas dineron que los que si pusieron algon en el pozo comun.” “Tercero. Si la gran mayoria no pone nada en el pozo comun, pero alguien si pone dinero en el pozo comun, las pocas personas que pongan dinero en el pozo comun tendran menos dierno que las personas que no pusieron nada.” “Cuarto. Si dos grupos estan compitiendo uno contra otro. Entonces el grupo que pone mas dinero en el pozo comun gana. Y cada persona en el grupo ganador recivira 1 dolar extra.” “Ahora te voy a hacer algunas preguntas sobre este juego.” “Que es lo que cada persona tiene que decidier sobre las 10 monedas de 25 centavos?” “Despues de que cada jugador haya decidio cuanto dinero poner en el pozo comun que el lo que yo hare despues?” “Si dos grupos estan compitiendo uno contra otro, cual es el grupo que gana?” “Ahora vas a jugar el juego. Recuerda no hay buenas ni malas respuestas en este juego. Aqui estan tus 10 monedas de 25 centavo. Tienes que decider cuanto de estas 10 monedas de 25 centavos quiers poner en el pozo comun y cuantas quieres quedarte contigo. Recuerdas puedes poner nada en el pozo comun si asi lo quieres. Si deseas puedes poner cualquier cantidad de tus 10 monedas en el pozo comun.” “Para este juego las personas de tu grupo son …” “Un (ingroup) y dos (outgroup)” (T1): “Sin competencia con ningun grupo” (T2): “Compitiendo con un grupo similar” “Tres (ingroup)” (T3): “Sin competencia con otros grupos” (T4): “Compitiendo con un grupo solo de (ingroup)” (T5): “Compitiendo con un grupo solo de (outgoup)” “Por favor pon la cantidad que desees dar al pozo comun al otro lado de la linea. Y lo que quieras quedarte de este lado. Gracias.” “Ahora vamos a jugar de nuevo. Las reglas son las mismas la diferencia es que esta vez las personas con las que vas a jugar son diferentes a las del juego anterior.” “Gracias has terminado del juego.” “Recuerda algunas personas no han jugado este juego todavia. No puedes hablar con nadie, si hablas con alguien el juego no puede seguir y las personas que no ha jugado no podra jugar. No puedes hablar de este juego sino hasta el martes, despues de que todos hayan jugado.” Te agradecemos nue.”
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