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Cooperation in an Uncertain World: For the Maasai of East Africa, Need-Based Transfers Outperform Account-Keeping in Volatile Environments


Abstract and Figures

Using an agent-based model to study risk-pooling in herder dyads using rules derived from Maasai osotua (“umbilical cord”) relationships, Aktipis et al. (2011) found that osotua transfers led to more risk-pooling and better herd survival than both no transfers and transfers that occurred at frequencies tied to those seen in the osotua simulations. Here we expand this approach by comparing osotua-style transfers to another type of livestock transfer among Maasai known as esile (“debt”). In osotua, one asks if in need, and one gives in response to such requests if doing so will not threaten one’s own survival. In esile relationships, accounts are kept and debts must be repaid. We refer to these as “need-based” and “account-keeping” systems, respectively. Need-based transfers lead to more risk pooling and higher survival than account keeping. Need-based transfers also lead to greater wealth equality and are game theoretically dominant to account-keeping rules.
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Cooperation in an Uncertain World: For the Maasai of East
Africa, Need-Based Transfers Outperform Account-Keeping
in Volatile Environments
Athena Aktipis
&Rolando de Aguiar
&Anna Flaherty
&Padmini Iyer
Dennis Sonkoi
&Lee Cronk
Published online: 3 May 2016
#The Author(s) 2016. This article is published with open access at
Abstract Using an agent-based model to study risk-pooling
in herder dyads using rules derived from Maasai osotua (Bum-
bilical cord^) relationships, Aktipis et al.(2011) found that
osotua transfers led to more risk-pooling and better herd sur-
vival than both no transfers and transfers that occurred at
frequencies tied to those seen in the osotua simulations.
Here we expand this approach by comparing osotua-style
transfers to another type of livestock transfer among Maasai
known as esile (Bdebt^). In osotua, one asks if in need, and one
gives in response to such requests if doing so will not threaten
ones own survival. In esile relationships, accounts are kept
and debts must be repaid. We refer to these as Bneed-based^
and Baccount-keeping^systems, respectively. Need-based
transfers lead to more risk pooling and higher survival than
account keeping. Need-based transfers also lead to greater
wealth equality and are game theoretically dominant to
account-keeping rules.
Keywords Need-based transfers .Account-keeping
transfers .Risk pooling .Herd survival outcomes .Maasai .
East Africa
People everywhere have to deal with both predictable and
unpredictable risks to their livelihoods. From modern day
humans grappling with uncertainties about health and em-
ployment, to Maasai pastoralist managing large herds in the
face of potential drought, disease and theft, risk management
is an important adaptive problem for humans around the
world. Humans use many strategies to manage risk, including
risk retention (accepting risk and absorbing losses), risk avoid-
ance (reducing dependence on high variability outcomes), risk
reduction (lowering the probability of or size of losses) and
risk transfer (moving risk from one party to another)
(Dorfman 2007). Risk transfer is of particular interest to social
scientists because it is the only one of these methods that
requires cooperation. One common form of risk transfer is
risk-pooling (also referred to as risk-sharing). Here we use
two different types of livestock transfer found among
Maasai pastoralists in East Africa to examine whether some
rules regarding such transfers lead to more risk-pooling and
more effective risk management than others.
We build upon Aktipis et al.(2011), which used an
agent-based model to examine the impact of stock friend-
ships on risk-pooling and herd survival among East African
pastoralists. That model was based specifically on the rules
underlying Maasai stock friendships, which they refer to by
their word for umbilical cord: osotua. The rules that govern
osotua relationships are straightforward: Ask only if you
are in need and only for what is needed, and give if you
are able to do so without threatening your own survival.
The model showed that pairs of herders that follow the
rules of osotua had herds that survive longer in the face
of occasional shocks than pairs that either engage in no
livestock exchange or that exchange livestock probabilisti-
cally at rates derived from the osotua simulations. In this
article, we expand our understanding of dyadic livestock
exchange among Maasai by comparing osotua transfers
with transfers Maasai refer to as esile, which translates
simply as Bdebt^(Mol 1996).
*Lee Cronk
Arizona State University, Tempe, AZ 85281, USA
Rutgers University, New Brunswick, NJ, USA
Hum Ecol (2016) 44:353364
DOI 10.1007/s10745-016-9823-z
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Maasai and other Maa-speaking pastoralists engage in sev-
eral different types of livestock transfers, each of which fol-
lows a different set of rules. In addition to bridewealth pay-
ments, osotua, and esile, these include enkitaaroto, in which
animals are put in someone elses herd but without a transfer
of ownership, ketaaro or elipa, in which a milking cow is lent
to a household in need, aitogaroo, in which a bull is lent for
breeding purposes, and keitapashaki, in which animals are
exchanged immediately, usually so that an individual can ob-
tain a steer for ceremonial purposes (Perlov 1987:173188).
Here we focus solely on osotua and esile, which have very
different underlying logic and rules. When osotua partners
transfer livestock, no debt is created, and it is inappropriate
to talk about either debt or payment. Osotua partners have
obligations to help one another, but the flow of goods and
services between them does not need to be even roughly bal-
anced over time (Cronk 2007). In transfers following the rules
of esile, debt and repayment are of the essence. Esile means
debt, and repayment is expected in the form of an animal at
least as valuable if not more so than the one given. The repay-
ment is referred to as elaata, which means to set free or untie a
knot (Perlov 1987:184). If a debtor fails to repay, his creditor
has the option of forgiving the debt but then referring to him
henceforth as BPasile^: One whose debt I have forgiven. This
type of construction, in which the prefix Bpa^is used to indi-
cate what a person has given or received, is common in Maa,
but it is normally used in a positive way. For example, a man
refers to his father-in-law as BPakiteng,^meaning Bcow re-
ceiver.^The use of the term BPasile^essentially serves as a
mild public reproach to those who fail to repay their debts. If
debts are not repaid before the debtor dies, they are passed on
to his heirs.
In principle, risk pooling could be accomplished via a va-
riety of different resource transfer rules. Here we focus on two
rules that can lead to the pooling of risk: osotua and esile.
Because many pastoralists other than the Maasai also have
rules that are equivalent to osotua and esile (Almagor 1978;
Bollig 1998,2010; Dyson-Hudson 1966; Flannery et al.1989;
Gulliver 1955), in an effort to generalize our terminology we
will henceforth refer to these not by their Maa labels but rather
as Bneed-based transfers^and Baccount keeping.^Here we
examine the underlying logic of both account keeping and
need-based transfers and use an agent-based model to com-
pare them in terms of their ability to enhance survival in vol-
atile environmental conditions.
This model is adapted from Aktipis et al.s(2011) agent-based
model of risk pooling among Maasai pastoralists. That model
was constructed to examine herd survival in volatile ecologi-
cal conditions characteristic of East African pastoralism (Dahl
and Hjort 1976; Homewood 2008). Here, in addition to incor-
porating account-keeping rules, we also generalize this model
by exploring a wider variety of ecological conditions. All
parameter values and assumptions about resource volatility
were initially drawn from Aktipis et al.(2011) and Dahl and
Hjort (1976), but were then varied to investigate our questions
of interest.
We used Netlogo software to model a population of two
actors, each with a herd of finite size. Each actor represented a
household/family of approximately six individuals and began
with a herd of 70. Although Maasai and other Maa-speaking
pastoralists keep a variety of different types of livestock (cat-
tle, goats, sheep, donkeys, and, in some arid areas, camels), in
an effort to keep our model simple and tractable we refer
simply to Bstock.^Given that the Maasai economy is domi-
nated by cattle, it would make the most sense for the reader to
think of the Bstock^in our model as cattle. During each time
period, each actors resource stock grew or shrank at a rate
normally distributed around a mean of 3.4 %, a typical annual
growth rate (Dahl and Hjort 1976). Maximum herd size was
600, a realistic maximum herd size for an average sized house-
hold. During each period there was a chance that each herd
would suffer a loss through drought or disease. As in Aktipis
et al.(2011), we also ran additional simulations in which we
varied the volatility size from zero to 50 % and the volatility
rate from zero to 20 %. Based on estimates of a familys
caloric needs and productivity in the dry season (Dahl and
Hjort 1976), we set the minimum size of a viable herd at 64.
Although this is high compared to the living standards of some
Maa-speaking pastoralists (e.g., Cronk 2004), the exact num-
ber is not important so long as it is consistent across all con-
ditions. Importantly, this figure is also consistent with Aktipis
et al.(2011)(Fig.1and Appendix).
We then simulated account-keeping-based and need-based
livestock transfers between individuals. In order to establish a
baseline for comparison, we first ran simulations in which no
transfers occurred. For runs involving the transfer of livestock,
we simulated interactions among individuals of the same type
as well as individuals of different types.
Below we describe the algorithms underlying need-based
transfers and account keeping. Account keeping requires the
tracking of debt and credit over time while need-based trans-
fers require individuals only to know their own resource
Need-based transfer rules were implemented as follows
(consistent with Aktipis et al.2011):
1. Need-based asking rule: Individuals ask their partners
for livestock only if their current holdings are below the
asking threshold (i.e., the minimum stock size of 64).
2. Need-based giving rule: Individuals give what is asked,
but not so much as to put their herds below the giving
threshold (also the minimum stock size of 64).
354 Hum Ecol (2016) 44:353364
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Account-keeping rules were implemented as follows:
1. Account-keeping payback rule:
a. If livestock have been previously transferred
from the partner to the actor and the actor has
enough to pay back without going below sus-
tainability threshold (resource min), the actor
pays backlivestock to his partner according
to the actorsrepayment probability
2. Account-keeping partner credit check rule:
a. Checks whether partner is in good standing, which
includes not having exceeded tolerated delay or credit
size (when applicable)
3. Account-keeping asking rule:
a. As with the need-based transfer asking rule, individ-
uals ask their partners for livestock if their current
herd size is below the sustainability threshold of 64.
4. Account-keeping giving rule:
a. Response to partner- If a request is made, actors give
if two conditions are met:
i. If no debt remains from a previous request and part-
had not existed for longer than tolerated delay)
ii. The amount transferred cannot exceed the credit
size extended to the partner
We then compared the performance of pairs of need-based
transfer individuals with other types of pairs including no
exchange pairs, account-keeping pairs and mixed pairs.
Additional details regarding the model schedule, parameter
values and model design can be found in the appendix.
Survival of Need-Based-Transfer Pairs vs.
Account-Keeping Pairs
We compared median survival of pairs of need-based transfer
individuals, account-keeping individuals and no-exchange in-
dividuals under the ecological conditions specified in the
model description. We found that pairs of need-based transfer
individuals had higher rates of herd survival than account-
1. Stock grows
Herds increase in size
according to growth rate
2. Potential
disaster strikes
Herds decrease in size
by volatility size every
volatility rate years
3. Requests made
Requests are made
according to account-
keeping or need-based
transfer rules
4. Resources
Livestock transferred
according to account-
keeping or need-based
transfer rules
5. Check viability
If holdings are below
herd min for two
consecutive years, the
individual is no longer
Fig. 1 Overview of model
schedule. The full model schedule
is included in the appendix
Hum Ecol (2016) 44:353364 355
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keeping pairs or pairs in which partners did not transfer re-
sources (Fig. 2).
Correlations of Survival Durations Within Pairs
In order to better understand whether individuals pool risk
more effectively under need-based transfer rules than under
account-keeping rules, we compared the median herd survival
experienced by one individual in a simulation to that experi-
enced by the other individual in the same simulation under
four different conditions: (1) no exchange, (2) two account-
keeping agents, (3) one account-keeping and one need-based
transfer agent, and (4) two need-based transfer agents (Fig. 3).
We found no correlation between survival durations when
individuals did not make transfers, but highly significant cor-
relations between the fates of the individuals when they did
transfer livestock. Specifically, when both individuals used
need-based transfer rules, correlations of their survival were
higher (ρ=0.54) than when both individuals used account-
keeping rules (ρ= 0.40). This indicates that, in addition to
being more effective than account-keeping at keeping live-
stock alive, need-based transfers also lead to a tighter yoking
of the fates of the two parties in the risk-pooling relationship.
Effects of Varying Environmental Volatility on Survival
In our baseline model, the likelihood and severity of losses
were normally distributed around 30 % and 10 %, respective-
ly. Given that the frequency of droughts in parts of East Africa
has been increasing (Homann et al.2008;Richéet al.2009),
we also looked at what happens when we vary the volatility
size and volatility rate across simulations for pairs of account-
keeping individuals and pairs of need-based transfer individ-
uals (Fig. 4). When volatility is very low, all individuals sur-
vive and when it is very high all individuals die. At all values
located between those two extremes, need-based transfer in-
dividuals survive longer than account-keeping individuals.
Effects of Generosity on Survival
In the osotua system, need-based transfers in their ideal form
are always generous, i.e., individuals always give if they are
asked and can do so without going below their own sustain-
ability thresholds. We investigated whether the success of the
need-based transfer rule was critically reliant on having 100 %
generosity (Fig. 5). We varied the generosity of need-based
transfer individuals and account-keeping individuals to com-
pare the viability of these strategies. For need-based transfer
0 25 50 75 100
Rounds (years)
Median proportion of herds surviving
Need−based transfers
Account keeping
No transfers
Fig. 2 Need-based transfer pairs
(red) show higher overall survival
than account-keeping pairs (blue).
Both need-based transfers and
account keeping have higher
survival than pairs in which no
exchange occurs (green)
Fig. 3 Pairs of need-based transfer individuals (bottom right) show
greater correlations of herd survival durations than account-keeping
pairs, no-exchange pairs or mixed pairs. Spearmans rank correlations,
n= 10,000 per condition: no-transfer condition ρ=0.01, n.s.; account-
keeping ρ=0.40, p0; heterogeneous strategies ρ=0.45, p0; need-
based transfers ρ=0.54,p0. p-values for all transfer conditions < 10
356 Hum Ecol (2016) 44:353364
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individuals, generosity was the likelihood of giving if asked
and able. For account-keeping individuals generosity was the
likelihood of giving to a partner in good standing if asked. We
found (1) that neither the account-keeping rule nor the need-
based transfer rule consistently outperforms no exchange un-
less generosity is at least 80 % and (2) that, when generosity is
high, pairs using the need-based transfer rule outperformed
pairs using the account-keeping rule. Without generosity,
need-based transfers are no more successful than account
Survival in Mixed Pairs
Under ecological conditions characterized by resource volatil-
ity, pairs using a need-based transfer strategy can outperform
pairs using an account-keeping strategy. The relationship be-
tween the need-based transfer and account-keeping strategies
is similar to the Stag Hunt Game (Skyrms 2003). Both strat-
egies are coordination points, but two individuals using the
need-based transfer strategy are likely to survive longer than
two individuals using the account-keeping strategy (Fig. 6).
Fig. 4 a Need-based transfers
outperform account keeping most
clearly when volatility size is
between 20-30 % of total
holdings. bSimilarly, need-based
transfers have the greatest
advantage over account keeping
when volatility rate is between 5-
10 % per year. Shaded regions
represent 95 % confidence
Fig. 5 Need-based transfer pairs
outperform account-keeping pairs
only when generosity is 80 % or
higher. Generosity is the
likelihood of giving if asked by
ones partner and one is able
(need-based transfers)ortoa
keeping). Shaded regions
represent 95 % confidence
Hum Ecol (2016) 44:353364 357
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The situation is thus a coordination problem that can be solved
if all the individuals know both that there is a solution and that
everyone involved also knows the solution (Chwe 2001;
Cronk and Leech 2013). In the real world, common knowl-
edge about need-based transfers can easily be provided by
sharing norms such as the osotua concept that focus on the
recipients need rather than on debt and repayment.
Wealth Inequality
In our model, stochastic growth and volatility of resources
create wealth inequality. Inequality is often measured using
the Gini coefficient (Gini 1912), which varies from 0 (when
wealth holdings are equal) to 1 (when one person controls all
the wealth). For comparative purposes, the highest Gini coef-
ficient in the world is currently 0.632 (Lesotho), and lowest is
0.230 (Sweden). The figure for the United States is 0.45
(Central Intelligence Agency 2013). We find that need-based
transfer individuals have the lowest inequality compared to all
other individuals (Fig. 7). Wealth inequality is highest in the
absence of wealth transfers (.576), followed by account-
keeping individuals (.516), and need-based transfer
individuals (.418). The Gini coefficient for need-based transfers
(.418) is similar to that found for a sample of pastoralist societies
(.42 ± .05) in a recent analysis of wealth inequality in societies
with subsistence economies (Borgerhoff Mulder et al.2009).
Inspired by the Maasai osotua system, Aktipis et al.(2011)
used an agent-based model to test whether a need-based trans-
fer rule leads to risk pooling and enhanced survival in volatile
ecological conditions. Here we extended this model to test
whether need-based transfer rules also outperform account-
keeping in risky environments. We found that need-based
transfers lead to greater risk pooling, longer survival and
greater wealth equality than account-keeping, though both
strategies outperformed scenarios involving no transfers of
Need-Based Transfers and Balanced Reciprocity
Reciprocity has been an important topic in economic anthro-
pology since the days of Malinowski (1922), Mauss (1967),
and Polanyi (1957). A common framework for understanding
different types of reciprocity is Sahlins(1965)trichotomyof
generalized, balanced, and negative reciprocity. Balanced rec-
iprocity corresponds fairly closely with what we have been
calling Baccount keeping.^We chose Baccount keeping^over
balanced reciprocity in order to emphasize and capture the
importance of debt and repayment in Maasai esile transfers.
Our focus has been on the contrasts between account-keeping
reciprocity and need-based transfers. Both of these patterns
may be adaptive responses to individual needs that are
Player 2
Need-based Account-keeping
Player 1
Need-based 30, 30 23, 29.5
Account keeping 29.5, 23 25, 25
Fig. 6 Payoffs in terms of survival at 50 years (in %) for individual and
partner using each rule in ecologically realistic environmental conditions.
The need-based transfer strategy is dominant to the account-keeping
Fig. 7 Stable differences in
inequality exist between transfer
strategies. Individuals engaging in
no transfers (green)havethe
highest level of inequality,
followed by account-keeping
individuals (blue) and then dyads
composed of need-based transfer
individuals (red). The straight line
(gray) shows perfect equality
358 Hum Ecol (2016) 44:353364
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asynchronous among individuals. When individualsneeds all
occur at the same time, neither account-keeping nor need-
based transfers beyond close kin would likely be adaptive.
But when needs arise asynchronously, it may make good
adaptive sense for those with resources to transfer them to
those without. The difference between need-based transfers
and account-keeping becomes apparent when we consider
the predictability of the needs in question. When needs are
both asynchronous and highly predictable, account-keeping
makes sense. If I know that I will always be in need on
Tuesday and you know that you will always be in need on
Friday, we can easily set up a system of balanced, tit-for-tat,
account-keeping reciprocity that benefits us both. But if needs
are not only asynchronous but also unpredictable, need-based
transfers may, as our model suggests, make more adaptive
sense than account-keeping. In short, when information about
future needs is good, account-keeping may reign, while need-
based transfers may prevail when such information is poor or
nonexistent, as it was in our model. In developed economies,
unpredictable needs are dealt with largely via formal insurance
markets. Insurance companies overcome the problem of poor
information about each individuals needs by gathering large
amounts of data about needs (rates of car accidents, home
fires, etc.) of many people. That allows them to focus on the
accuracy of data about needs in the aggregate rather than on
the inaccuracy of data regarding each individualsneeds,
which in turns allows them to set rates and engage in
account-keeping exchanges with their clients (Levy 2012).
Need-Based Transfers and Generalized Reciprocity
In Sahlinsgeneralized reciprocity, sharing is indiscrim-
inate and widespread. The same idea is also captured by
FiskesBcommunal sharing^(Fiske 1991). Generalized
reciprocity and communal sharing are good descriptions
of how resources are often shared within households
and within hunter-gatherer bands (e.g., Howell 2010;
Woodburn 1998;Price1975). However, neither is an
accurate description of osotua relationships or other
stock friendship relationships among pastoralists. Such
relationships are characterized not by indiscriminate
and widespread sharing but rather by limited contractual
commitments between individual livestock owners. The
advantage of the phrase Bneed-based transfers^is that it
captures both of these patterns, which focuses our atten-
tion on the fact that risk-pooling results from both of
them. This, in turn, provides a link between the study
of need-based transfers and the existing literatures on
risk-pooling in both anthropology (Bird and Bird 1997;
Bliege Bird et al.2002; Cashdan 1985; Gurven et al.
2000; Gurven and Hill 2009,2010; Wiessner 1982;
Winterhalder 1986) and economics (e.g., Barr and
Genicot 2008; Fafchamps and Lund 2003).
Computational Simplicity of Need-Based Transfers
In addition to its effectiveness in pooling risk, need-
based transfer systems also have low cognitive load.
Need-based transfer rules are simple: Ask if you need,
give if you can. The rules underlying a tit-for-tat,
account-keeping strategy can be straightforward in a
Prisoners Dilemma framework (Axelrod 1984), but they
prove much more complex in the more realistic situation
we sought to model. In contrast to the simple rules
followed by the need-based transfer agents, the
account-keeping agents must follow a complex set of
rules regarding such issues as credit, debt and repay-
ment. Account-keeping agents use memory of their past
transactions with other agents, whereas need-based
transfer agents simply need to keep track of whether
their own resource holdings are above their survival
threshold and occasionally calculate whether they can
afford to help a partner in need. The low cognitive
requirements of need-based transfer systems suggest that
they may have predated account-keeping in our species
evolutionary history and could be more phylogenetically
widespread than systems requiring account-keeping.
Cheating and the Evolution of Cooperation
Organisms who live socially have the ability to manage risk
through risk pooling, enabling them to live in more challeng-
ing ecological conditions by sharing resources during times of
need. However, as with other explanations for the evolution of
cooperation, the problem of cheating must be addressed.
The vast literature on cheater detection and cheater
suppression has largely been motivated by solving the
problem of cheating in the context of account-keeping
interactions (Cosmides and Tooby 1992; Van Lier et al.
2013). Cheating in the context of need-based transfer is
different, however, from cheating in an account-keeping
system. In an account-keeping system, cheating is typi-
cally a matter of not repaying onesdebts.Inaneed-
based transfer system, unbalanced accounts do not con-
stitute cheating. Rather, cheating in a need-based trans-
fer system involves asking for help when one is not in
need or refusing to give when one is able. These dif-
ferent criteria for what constitutes cheating are another
important way in which need-based transfers differ from
account keeping.
Need-based transfers can be conceptualized as a form
of decentralized and informal insurance. One of the
problems that can arise when individuals have insurance
in general is the problem of moral hazard, i.e., when
individuals become more prone to take risks and act
less carefully because they do not bear all the costs
associated with a bad outcome. In this sense, the moral
Hum Ecol (2016) 44:353364 359
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hazard problem may be at the heart of another way of
cheating in a need-based transfer system: if being re-
sponsible and careful is costly, one can cheat by being
lazy and taking unwise risks, knowing that one will
receive help if the outcome is a severe loss or catastro-
phe. Interestingly, in the Maasai osotua system, individ-
uals are also expected to act with responsibility, restraint
and respect in how they handle their herds (Cronk
2007). In other words, they are expected to behave in
such a way that may help to solve the moral hazard
problem and minimize this type of cheating that is pos-
sible in systems of need-based transfers.
Another way of suppressing cheating is for individ-
uals to carefully choose partners with whom they enter
into need-based transfer relationships. Partner choice is
one way of enhancing assortment of cooperators with
one another, and it can be realized through both simple
and complex rules for choosing and maintaining rela-
tionships (Aktipis 2004,2006,2011; Barclay 2013;
Barclay and Willer 2007;Nesse2009;Noeand
Hammerstein 1994). Among the Maasai, need-based
transfer relationships are taken very seriously and are
said to be unbreakable once formed. Partner choice
mechanisms could be at work in relationship formation
if individuals can evaluate others through observing
their behavior or reputations before entering into rela-
tionships in which they are committed to help.
Choosing need-based transfer partners that have comple-
mentary risk profiles (i.e., independence of shocks) and
responsible practices has high stakes. Discerning partner
choice is therefore likely to play an important role in
the viability of need-based transfer systems.
Need-based transfer systems require that individuals
stay committed to helping a partner if that partner is
unlucky; however, there may be conditions under which
it is acceptable to terminate a need-based transfer rela-
tionship. These conditions may allow for dissolving re-
lationships with greedy, stingy or irresponsible individ-
uals (though not unfortunate ones). Relationship disso-
lution rules could thus provide another partner choice
mechanism that could reduce cheating in need-based
transfer systems. This is a research question that we
will address in future fieldwork and modeling.
Finally, cheating in need-based transfer systems may
be made difficult simply by the public nature of certain
kinds of wealth. For example, among foragers, the same
kinds of foods that are the most variable from day to
game animals) are also the ones that are the most dif-
ficult to conceal. Among Maasai and other pastoralists,
wealth primarily takes the form of livestock, whose vis-
ibility may make it difficult for anyone to feign either
need or an inability to help. Despite the visibility of
livestock, it would in principle be possible to hide ones
wealth by taking advantage of practices such as
enkitaaroto, a Maasai system in which animals are put
in someone elses herd but without a transfer of owner-
ship. We have livestock census data from two East
African pastoralist societies, the Mukogodo Maasai of
Kenya (Cronk 1989,2004) and the Karimojong of
Uganda. In both cases, the correlation between herders
apparent wealth, defined as the numbers of animals in
their herds regardless of who really owns them, and
actual wealth, defined as the number of animals that
they actually own regardless of whose herd they happen
to be in, is too high for this kind of cheating to be a
problem (Mukogodo Maasai: Pearsonsr=0.984,
p< 0.01, N= 183; Karimojong: Pearsons r = 0.968,
p<0.01, N= 44). In systems where resources can be
hidden or individuals are otherwise unable to evaluate
the resource holdings of others, cheating in need-based
transfer systems is likely to be a larger problem.
Effectively managing risk and uncertainty are recurring adap-
tive problems across human societies. One way of managing
the risks associated with life in volatile ecologies is to pool
risk with others. Here we show that need-based transfers out-
perform account-keeping rules and can be effective even when
implemented in computationally simple terms.
Acknowledgments This material is based upon work supported by the
National Science Foundation under Grant No. SES-0345945 to Arizona
State Universitys Decision Center for a Desert City (DCDC) and Grant
No. BCS-1324333 to Cronk and Iyer, National Institute of Health Grant
No. F32 CA144331, and a grant from the John Templeton Foundation.
We thank the Institute for Advanced Study in Princeton, the Center for
Theological Inquiry in Princeton, the Center for Advanced Study in the
Behavioral Sciences at Stanford University and the Wissenschaftskolleg
in Berlin. We would also like to thank participants in the National
Evolutionary Synthesis Center catalysis meeting for Synthesizing the
Evolutionary and Social Science Approaches to Human Cooperation,
the members of the Human Generosity Project and the members of the
Cronk and Aktipis lab groups. Any opinions, findings, conclusions, or
recommendations expressed in this material are those of the authors and
do not necessarily reflect the views of the National Science Foundation
(NSF), the National Institute of Health (NIH), or the John Templeton
Compliance with Ethical Standards
Funding This material is based upon work supported by the National
Science Foundation under Grant No. SES-0345945 to Arizona State
Universitys Decision Center for a Desert City (DCDC) and Grant No.
BCS-1324333 to Cronk and Iyer, National Institute of Health Grant No.
F32 CA144331, and a grant from the John Templeton Foundation to
Aktipis and Cronk.
Conflict of interests The authors declare that they have no conflicts of
360 Hum Ecol (2016) 44:353364
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Model Description The model description offered below fol-
lows the standardized ODD protocol for describing individual and
agent based models (Grimm et al.2006) and is based on Aktipis
et al.(2011).
Purpose Here we use an agent-based model of wealth transfers
within ecologically realistic conditions to investigate the viability
of two sets of cooperative rules: one characterized by account
keeping and the other characterized by risk pooling norms of
need-based transfers. We then investigate how these two rules
affect overall resource stock survivorship and the variability of
survivorship within dyads.
State Variables and Scales In this model time is represented
discretely. Space is not explicitly modeled. Resource stock
growth dynamics and volatility are implemented with global
variables while the resource stock size and giving/asking rules
are agent variables (Table 1). During each time period, agents
execute the commands described in the schedule.
Process Overview and Scheduling This model proceeds in
discrete time steps, and entities execute procedures according to the
following ordering:
1. For each actor, resource stocks change in size:
a. Resource stocks increase in size according to growth rate
b. Resource stocks decrease in size by volatility size (as a percent of
total holdings) according to volatility rate
c. If resource stock size is above resource stock max it is set to resource
stock max
d. Resource stock size is rounded to nearest integer
2. Requests are made:
&If giving is need-based, requests are made if resource stock size
is below resource stock min
&If giving is account-keeping-based, requests are made if re-
source stock size is below resource stock min
3. Transfers are made:
&If giving is need-based, requests are fulfilled to the extent possible
keeping the resource stock size of the giver above resource stock min
&If giving is account-keeping-based
If resources have been previous transferred from the partner to
the actor, the actor transfers net received resources to their
partner according to repaym ent prob
If a new request was made, actors give if two conditions are met
The debt has not existed for longer than tolerate d delay
The amount transferred cannot exceed the credit size extended
to the partner.
&All actors update net received to reflect transfers
4. Actors removed from the population if two consecutive rounds occur
where resources holdings are below resource stock min.
Tabl e 1 Overview of state
variables associated with each
Entity State variable Description
Global Growth rate Amount by which resource stocks grow each year
Volatility rate Likelihood of a negative event (e.g., drought)
Volatility size Decrease in resource stock size resulting from negative
Min. resource stock
The minimum viable resource stock size
Max. resource stock
The maximum resource stock that can be maintained
Agents Resource stock size
Net received
Number of resources in agents resource stock
Number of resources received minus given to partner
Asking threshold The threshold below which agents ask for resources
Generosity The likelihood of giving if asked and able (need-based)
or giving to partner in good standing (account-keeping)
Need-based only Giving threshold The threshold below which agents will no longer give
Credit size The amount of credit granted to partner
Tolerated delay The number of periods an agent will tolerate not being
repaid by partner before placing partner in bad standing
P good standing If partner is in good standing, means that they have
not exceeded tolerated delay in past transfers
Repayment probability The likelihood of repaying partner during each time period
Hum Ecol (2016) 44:353364 361
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5. Age of actors incremented by 1
Design Concepts
Emergence In this model, risk pooling emerges from interactions
between agents.
Prediction Agents in this model lack the ability to predict outcomes
of future environmental variability or future social interactions. They do
not integrate information across time periods.
Sensing Agents receive requests from their interaction partners and
are able to examine theirown resource holdings before fulfilling requests.
Interaction Agents interact by making and fulfilling requests for
Stochasticity Resource stock growth and environmental volatility
both have stochastic components.
Observation Reported data are averaged from 10,000 runs.
Simulations were run until both agents were removed from the population
(i.e., dropped below the viability threshold for more than 2 consecutive
time periods).
Initialization All runs were initialized according to default
parameters in the table below (Table 2).
Input In order to make our model of the Maasai pastoral system as
realistic as possible, the following parameter values and assumptions
about resource dynamics were based on existing scholarship (Dahl and
Hjort 1976).
Growth rate We used a 3.4 % growth rate with an SD of 2.53 based
on Dahl and Hjorts(1976:66) estimate the growth rate in Bnormal^con-
ditions to be 3.4 %, with a maximum possible growth rate of roughly
11 % and a minimum of approximately 6 % (in the diminishing resource
stocks example). Dahl and Hjort estimates are based on both empirical
evidence and analytical modeling.
Resource stock size Initial resource stock sizes in our model were
70, with a minimum of 64 and a maximum of 600. These values were
derived from Dahl and Hjort (1976:178) who state that a resource stock of
64 resources is sufficient to sustain a reference family. Resource stock
sizes described in the text range from 60100 cows and resource stocks
larger than 600 are not considered viable (Dahl and Hjort 1976:158).
Volatility We used a volatility rate of .1, meaning that on average a
disaster (e.g., drought or disease) occurred every 10 years. In our model,
this disaster reduced the resources resource stock by 30 % on average,
with a SD of 10 %. Dahl and Hjort (1976:114130) note that these disas-
ters occur approximately every 1012 years based on empirical data, and
that the population decline (during disasters that occur every 10 years)
should not bemore than approximately 28 %, based on analytical models.
Tabl e 2 Initial and default values
for all variables Entity State variable Initial/Default value Units
Global Growth rate 3.4 (SD: 2.53) % current resource stock
Volatility rate 10 % per year
Volatility size 30 (SD: 10) % of current resource stock
Min. resource stock size 64 Number resources
Max. resource stock size 600 Number resources
Agents Resource stock size 70 Number resources
Net received 0 Number resources
Asking threshold 64 Number resources
Generosity 100 % likelihood
Need-based only Giving threshold 64 Number resources
Account-keeping only Credit size 5 Number resources
Tol era ted d el a y 5 Year s
P good standing Yes Yes/No
Repayment probability 100 % likelihood
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... Agent-Based Models (ABMs) are often used to investigate emergent complex social phenomena and resource availability, as a function of environmental stress, on emergent cooperativebehaviour [5]- [7]. Also, ABMs are frequently used to study the emergence of social stratification (the grouping of people based on socioeconomic factors such as wealth, race and social status) in ancient societies [2], [8]. ...
... 3) Probability-Based Cooperation: These agents are an extension to the cooperative or defective agents described above where the likelihood of agents exhibiting cooperative or defective behaviour is recorded as some probability p [5], [12]. These ABMs typically include some form of learning allowing agents to adapt their p value in accordance with a predefined set or rules or fitness-based algorithms such as Evolutionary Algorithms [13]. ...
... ABM research directly related to ours includes Angourakis et al. [6] who studied the emergence of cooperative behaviour in scenarios with varying degrees of food storage efficiency, Pereda et al. [4] who studied the emergence of cooperation under varying degrees of environmental stress and Aktipis et al. [5] who compared need-based and account-keeping cooperation dynamics as they related to the Maasai of East Africa. More generally, Axelrod and Hamilton's [10] seminal work on the evolution of cooperation, Chliaoutakis and Chalkiadakis' [8] self-organizing agent hierarchies and Molin, Kanwal, and Stone's [7], study of emergent cooperation in spatially explicit environments are relevant to the study presented here. ...
... It has been hypothesized that people have evolved to form long-term relationships with non-genetically related individuals, in order to have around them others who could provide them with reliable support and assistance (Hruschka, 2010;Kruger, 2003;Tooby & Cosmides, 1996). In a similar hypothesis, making special types of friendships can be a form of social insurance against disaster (Aktipis, 2011;Aktipis et al., 2016;. To use one example, the Massai of East Africa have a system known as osotua, where they develop osotua friends. ...
... To use one example, the Massai of East Africa have a system known as osotua, where they develop osotua friends. In this system, when someone is in dire need, they can call their osotua friends for help, who if they can do so without harming their own chances of survival, are oblige to offer help (Aktipis et al., 2016). As this example indicates, having friends who can provide help in times of need, would be particularly helpful in a preindustrial context where there are no social support and protection systems, and people need the assistance of others if they are to deal successfully with the challenges of survival. ...
Not all friendships last a lifetime, and frequently, people choose to end them. The current research employed mixed-methods in order to identify the different strategies that people use in order to end an undesirable friendship, and the degree that the adoption of these strategies is predicted by personality. More specifically, Study 1 employed qualitative research methods on a sample of 225 Greek-speaking participants, and identified 43 acts that people would perform in order to end a friendship. Study 2 employed quantitative research methods on a sample of 469 Greek-speaking participants, and classified these acts into seven broad sub-strategies and three broader strategies for terminating an undesirable friendship. Participants indicated that they were more willing to use the "Gradual termination," and less willing to use the "Immediate termination" strategy. Moreover, higher scorers in agreeableness indicated a higher willingness to use the former and a lower willingness to use the latter strategy than low scorers. Additionally, although there were some significant differences, women and men as well as participants in different age groups, were generally in agreement over which strategy they were willing to use.
... Agent-based models (ABMs) have been used to analyse potential long-term effects of index insurance on the sustainability of rangeland management (Müller et al., 2011) and resulting pasture conditions (John et al., 2019). In other studies, the effectiveness of insurance through informal risk sharing (Aktipis et al., 2011(Aktipis et al., , 2016Campennì et al., 2021;Hao et al., 2015) and impacts of combining formal and informal insurance have been investigated. ...
... There exist successful examples of such back-and-forth approaches. Cronk et al. (2019), for instance, designed a two-player game to study risk pooling in a laboratory based on earlier ABMs of risk pooling in dyads (Aktipis et al., 2011(Aktipis et al., , 2016. The results from the game and ABMs were then used to inform the design of additional experimental games (Claessens et al., 2021). ...
Full-text available
Extreme weather conditions in the face of due to climate change often disproportionately affects the weakest members of society. Agricultural insurance programs that are specifically designed specifically for smallholders in developing countries are valuable tools that can help farmers to cope with the resulting risks. A broad range of methods including household surveys, experimental games, and agent-based models have been used to assess and improve the effectiveness of such climate insurance products. In addition Furthermore, process-based crop models have been used to derive suitable insurance indices. However, climate change raises specific socioeconomic andas well as environmental challenges that need to be considered when designing insurance schemes. We argue that, in light of these pressing challenges, some of the methodological approaches currently applied to study climate insurance reach their limits when applied independently. This has fundamental implications. On the one hand, not all undesired side effects of insurance can be detected and, on the other hand, insurance indices cannot be derived sufficiently well. We therefore advocate a sound combination of different methods, especially by linking empirical analyses and modelling, and underline the resulting potential with the help of stylized examples. Our study highlights how methodological synergies can make climate insurance products more effective in supporting the most vulnerable households, especially under changing climatic conditions.
... The ubiquity of need-based transfers across societies and their utility in allowing people to manage unpredictable risks suggest that the association between the perceived predictability of needs and whether people expect repayment for their help may be part of a broader human psychology that allows people to identify and manage risk. In support of this, agent-based models show that need-based transfers can lead to higher survival than debt-based transfers when shocks occur that lead to losses, creating needs that are hard to predict (Aktipis et al., 2016;Aktipis et al., 2011;Campennì et al., 2021). The success of needbased transfers is partially due to the fact that need-based transfer relationships, unlike debtbased transfer relationships, do not dissolve when someone does not pay back previous help. ...
... In addition, agent-based models have shown that need-based transfers are a more viable strategy than debt-based transfers when individuals encounter unpredictable shocks that lead to needing help (Aktipis et al., 2016;Aktipis et al., 2011;Campennì et al., 2021). ...
Full-text available
Sometimes people help one another expecting to be repaid, while at other times people help without an expectation of repayment. What might underlie this difference in expectations of repayment? We investigate this question in a nationally representative sample of US adults (N = 915), and find that people are more likely to expect repayment when needs are perceived to be more predictable. We then replicate these findings in a new sample of US adults (N = 417), and show that people have higher expectations of repayment when needs are perceived to be more predictable because people assign greater responsibility to others for experiencing such predictable needs (e.g., needing money for utilities). This is consistent with previous work based on smaller-scale societies, which shows that the predictability of needs influences expectations of repayment. Our results also add to this previous work by (1) showing that the positive relationship between predictability of needs and expectations of repayment previously found in smaller-scale communities is generalizable to the US population, and (2) showing that attributions of responsibility partially mediate this relationship. This work shows that the predictability of needs and attributions of responsibility for that need are important factors underlying the psychology of helping in times of need.
... Friendships are thought to provide benefits central to health, happiness, and well-being (Dunbar, 2018;Fehr, 1996;Hruschka, 2010;Perlman et al., 2015). For example, evolutionary researchers have documented that friendships provide support during conflicts (DeScioli & Kurzban, 2009, 2013, physical protection (Bleske-Rechek & Buss, 2001;Campbell, 1999;Lewis et al., 2011;Smuts, 1985), support in times of need (Aktipis et al., 2011(Aktipis et al., , 2016Gurven & Hill, 2009;Tooby & Cosmides, 1996;van der Horst & Coffé, 2012), cooperation through interdependence (Aktipis et al., 2018;Ayers et al., 2022), help with childcare (Hrdy, 2007), access to potential romantic partners (Bleske-Rechek et al., 2012;Mogilski & Wade, 2013), and help mitigating interpersonal conflict in romantic relationships (Keneski et al., 2018). ...
Friendships are valuable relationships that can bestow many benefits. How can humans ensure they receive the maximum benefits with minimal potential costs? One possible solution is to have preferences for traits, expectations, and rules in friendship. This could, for example, help people pursue beneficial friendships and jettison costly friendships. Previous research robustly documented that such preferences for traits, expectations, and rules exist, though they are often combined, and indicates that they may be sex-specific. Across two studies (N = 853), our factor analyses documented that preferences for desired traits in friendship are organized into two broad categories with women rating intrinsic traits as more important in their friendship come pared to men’s ratings. Similarly, factor analyses showed that preferences for rules in friendship are organized into four broad categories with women rating all rule categories as more important in their friendships compared to men’s ratings.
... They also fail to appreciate constraints a chosen network type (friendship, sharing, cooperating in different tasks) bring to bear on estimated network characteristics, which has rarely been examined [19], yet is critical to structuring network observables. For example, Aktipis and colleagues have shown that need-based livestock transfers among the Maasai are associated with different principles of cooperation than transfers based on 'accountkeeping' [70], even when the item being transferred is the same. This suggests that cooperative activities and their underlying goals exert strong influences on patterns that may be observed in cooperative networks in ways that are ( perhaps frequently) likely to supersede the differences attributable to gender, per se. ...
Full-text available
Cooperative networks are essential features of human society. Evolutionary theory hypothesizes that networks are used differently by men and women, yet the bulk of evidence supporting this hypothesis is based on studies conducted in a limited range of contexts and on few domains of cooperation. In this paper, we compare individual-level cooperative networks from two communities in Southwest China that differ systematically in kinship norms and institutions—one matrilineal and one patrilineal—while sharing an ethnic identity. Specifically, we investigate whether network structures differ based on prevailing kinship norms and type of gendered cooperative activity, one woman-centred (preparation of community meals) and one man-centred (farm equipment lending). Our descriptive results show a mixture of ‘feminine’ and ‘masculine’ features in all four networks. The matrilineal meals network stands out in terms of high degree skew. Exponential random graph models reveal a stronger role for geographical proximity in patriliny and a limited role of affinal relatedness across all networks. Our results point to the need to consider domains of cooperative activity alongside gender and cultural context to fully understand variation in how women and men leverage social relationships toward different ends. This article is part of the theme issue ‘Cooperation among women: evolutionary and cross-cultural perspectives’.
... For all other uses, contact the owner/author(s). GECCO commonly used to investigate the relationship resource availability, as a function of environmental stress, has on the emergence of cooperative-behaviour [1,2,6]. Additionally, ABM have also been used to study the emergence of social stratification [4,9,10]. ...
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In recent years there has been much research regarding the extent to which social status is related to long-term indices of health. The majority of studies looking at the interplay between social status and health have been conducted in industrialized societies. However, it has been argued that most of human evolution took place in small, mobile and egalitarian hunter-gatherer groups where individuals exhibited very little variation in terms of material wealth or possessions. In this study, we looked at the extent to which two domains of social status, hunting reputation (being perceived as a good hunter) and popularity (being perceived as a friend), are related to physiological stress levels among Hadza men, hunter-gatherers living in Northern Tanzania. The results of our study show that neither hunting reputation nor popularity is associated with stress levels. Overall, our data suggest that, in at least some traditional small-scale societies exhibiting an egalitarian social model, such as the Hadza, the variation in social status measures based on both popularity and hunting reputation does not translate into one of the commonly used indices of wellbeing.
Humans form and maintain friendships across long distances, which can provide access to non-local resources and support against large shocks that affect the entire local community. However, there may be a greater risk of defection in long-distance friendships, as monitoring for defection is more difficult at greater distances; accordingly, help between long-distance friends may be more explicitly contingent than between close-distance friends. We interviewed 918 participants from 21 fishing villages in Tanzania about whether they had received help in the form of a gift or loan from a friend living in their village and a friend living in a neighboring village. As there are local expectations that loans will be repaid but gifts will not, we predicted that close-distance friends would be more likely to help with gifts, whereas long-distance friends would be more likely to help with loans. Contrary to our predictions, gifts and loans between close- and long-distance friends were similar in kind and amount, though close-distance friends provided help more frequently, possibly because close-distance friends are more likely to meet frequently and belong to the same religious congregation. These results indicate that long-distance friendships are an important, and likely robust, strategy for managing risk and accessing more resources.
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The book was written in reaction to common misconceptions about how fast pastoral livestock herds could grow and about the logic of traditional livestock rearing in East Africa. It deals with human nutritional needs and the necessary sizes of herds and flocks kept for subsistence purposes, and with the rate of growth of herds of camels, cattle, sheep and goats. The advantages of herd diversification for food security are discussed.
This collection of articles aims at revitalizing the study of kinship and exchange in a social network perspective. It brings together studies of empirical systems of marriage and descent with investigations of the flow of material resources in societies of Africa, Asia, the Pacific and Europe. Restudies of classic ethnographic cases and fieldwork studies of kinship and exchange demonstrate how the social and material aspects of society are related, and address issues of concern to anthropology and the neighbouring disciplines of history, sociology and economics. This book marks the emergence of an era in the study of kinship and exchange using a productive combination of ethnographic substance with formal methods, one which leaves behind older structural-functionalist and culturalist assumptions.
Life Histories of the Dobe !Kung re-examines an important anthropological data set for the Dobe !Kung, the well-known "Bushmen" of the Kalahari Desert, collected by Nancy Howell and colleagues. Using life history analysis, Howell reinterprets this rich material to address the question of how these hunter-gatherers maintain their notably good health from childhood through old age in the Kalahari's harsh environment. She divides the population into life history stages that correlate with estimated chronological ages and demonstrates how and why they survive, even thrive, on a modest allotment of calories. She describes how surplus food is produced and distributed, and she considers both the motives for the generous sharing she has observed among the Dobe !Kung and some evolutionary implications of that behavior.
Why do Internet, financial service, and beer commercials dominate Super Bowl advertising? How do political ceremonies establish authority? Why does repetition characterize anthems and ritual speech? Why were circular forms favored for public festivals during the French Revolution? This book answers these questions using a single concept: common knowledge.Game theory shows that in order to coordinate its actions, a group of people must form "common knowledge." Each person wants to participate only if others also participate. Members must have knowledge of each other, knowledge of that knowledge, knowledge of the knowledge of that knowledge, and so on. Michael Chwe applies this insight, with striking erudition, to analyze a range of rituals across history and cultures. He shows that public ceremonies are powerful not simply because they transmit meaning from a central source to each audience member but because they let audience members know what other members know. For instance, people watching the Super Bowl know that many others are seeing precisely what they see and that those people know in turn that many others are also watching. This creates common knowledge, and advertisers selling products that depend on consensus are willing to pay large sums to gain access to it. Remarkably, a great variety of rituals and ceremonies, such as formal inaugurations, work in much the same way.By using a rational-choice argument to explain diverse cultural practices, Chwe argues for a close reciprocal relationship between the perspectives of rationality and culture. He illustrates how game theory can be applied to an unexpectedly broad spectrum of problems, while showing in an admirably clear way what game theory might hold for scholars in the social sciences and humanities who are not yet acquainted with it.
Brian Skyrms' study of ideas of cooperation and collective action explores the implications of a prototypical story found in Rousseau's A Discourse on Inequality. It is therein that Rousseau contrasts the pay-off of hunting hare (where the risk of non-cooperation is small and the reward equally small) against the pay-off of hunting the stag (where maximum cooperation is required but the reward is much greater.) Thus, rational agents are pulled in one direction by considerations of risk and in another by considerations of mutual benefit. Written with Skyrms' characteristic clarity and verve, The Stage Hunt will be eagerly sought by readers who enjoyed his earlier work Evolution of the Social Contract. Brian Skyrms, distinguished Professor of Logic and Philosophy of Science and Economics at the University of California at Irvine and director of its interdisciplinary program in history and philosophy of science, has published widely in the areas of inductive logic, decision theory, rational deliberation and causality. Seminal works include Evolution of the Social Contract (Cambridge, 1996), The Dynamics of Rational Deliberation (Harvard, 1990), Pragmatics and Empiricism (Yale, 1984), and Causal Necessity (Yale, 1980).
"From the family to the workplace to the marketplace, every facet of our lives is shaped by cooperative interactions. Yet everywhere we look, we are confronted by proof of how difficult cooperation can be--snarled traffic, polarized politics, overexploited resources, social problems that go ignored. The benefits to oneself of a free ride on the efforts of others mean that collective goals often are not met. But compared to most other species, people actually cooperate a great deal. Why is this? Meeting at Grand Central brings together insights from evolutionary biology, political science, economics, anthropology, and other fields to explain how the interactions between our evolved selves and the institutional structures we have created make cooperation possible. The book begins with a look at the ideas of Mancur Olson and George Williams, who shifted the question of why cooperation happens from an emphasis on group benefits to individual costs. It then explores how these ideas have influenced our thinking about cooperation, coordination, and collective action. The book persuasively argues that cooperation and its failures are best explained by evolutionary and social theories working together. Selection sometimes favors cooperative tendencies, while institutions, norms, and incentives encourage and make possible actual cooperation.