What are “Need-Based Transfers”?

What are “Need-Based Transfers”?

A Human Generosity Project blog post by Lee Cronk and Athena Aktipis

 April 11, 2016


Being a cowboy is a dangerous job. Day-to-day life involves constant grappling with forces much larger than themselves. The ranchers that we study in the Malpai borderlands region of Arizona and New Mexico thrive on their connections to the land and the outdoors, to the uncertain and awesome forces of nature that they experience every day, and to the animals that they ride and care for. But being a rancher also means being exposed to a variety of risks and hazards. Ranchers grapple not just with the uncertainties of the weather and local ecologies, but also with taming and harnessing wild forces that pose serious hazards. Daily interactions with horses, cattle, and heavy machinery all have the potential to injure and even kill, and accidents can happen even when they are taking all the proper precautions.

Our time with Malpai ranchers has taught us this if nothing else: Choosing to live the life of a cowboy is pretty much a guarantee that you’ll sustain at least one serious injury at some point in your life. That much is predictable. What is unpredictable is exactly when and where those injuries will occur, and to whom. When someone is injured so badly that he or she can’t work, finding someone with the right skill set to take over can be quite difficult. However, one reliable source of such skilled labor is right at hand: Neighbors. And, when injuries and other unpredictable events happen, neighbors in the Malpai region do step up and help each other with no expectation of any return other than the same kindness if they should ever happen to be in need.

Generosity toward those in need is, of course, not limited to Malpai ranchers. Indeed, it seems to be present, in one form or another, in practically every human society. Among Hadza hunter-gatherers in Tanzania, for example, food brought back to camp is shared widely without creating a sense of debt. Not far from the Hadza, Maasai pastoralists create relationships of generosity and mutual aid that they refer to by their word for “umbilical cord”: osotua. Osotua partners agree to help each other when in need, with no expectation of repayment. Within osotua relationships, use of the Maasai words for debt (esile) and to pay (alak) is expressly forbidden (Cronk 2007).

Among the Maasai and other societies that we study in The Human Generosity Project, these acts of sharing are characterized by two important rules: (1) ask only if you are in need and only for as much as you need, and (2) if asked, give up to the point that you are able without becoming needy yourself. These rules together make up what we call need-based transfer systems. Need-based transfers are characterized by giving that is conditional on the need of the recipient, not the recipient’s ability to repay the kindness.

Before we adopt the term “need-based transfers,” it’s worth asking whether we need to create new terminology or whether there is some existing term that we can use. There are certainly a lot of terms to choose from, from simply “sharing” to the more technical “risk reduction reciprocity.” Let’s look at some of these alternative terms to see whether they capture giving that is conditional on the need of the recipient.

First let’s consider the term “sharing.” Unfortunately, sharing is a broad concept that does not by itself capture the idea that the giving is to those in need. One can, after all, share with someone who is wealthy as easily as with someone who is poor. Perhaps, then, we could use a more technical term that is already in the literature that describes sharing within a community, such as Fiske’s (1991) “communal sharing.” Or how about Sahlins’ (1965) “generalized reciprocity”? These terms fit some cases of need-based transfers where individuals help others in their community or group, but they don’t describe the kinds of sharing that happens among the Maasai. The sharing that occurs between Maasai osotua partners does not involve widespread sharing but instead take place within a clearly defined framework in which livestock are private property that individuals transfer when one party makes a specific request for help.

How about “strong reciprocity,” a controversial term that its advocates use to refer to uncompensated generosity (Gintis 2000; cf. Burnham and Johnson 2005, Cronk and Leech 2013)? The problem is that proponents of strong reciprocity posit that it exists due to forces of group selection. While generosity toward those in need may indeed yield group-level fitness benefits, our work shows that, in the right circumstances, generosity toward those in need can be fitness-enhancing even at the level of the individual.

Why not “risk-reduction reciprocity” (Bliege Bird et al 2002)? In this instance, our objection is logical. The risk-pooling that results from need-based transfers does not actually reduce risk, so “risk-reduction reciprocity” would be a misnomer. Risk-pooling simply redistributes risk in a way that allows individuals to avoid catastrophic outcomes. By pooling risk, people exchange the small likelihood of a disastrous loss for the high likelihood of small, manageable losses. Need-based transfers are about risk management, not risk reduction, per se. Humans use many strategies for managing risk (Dorfman 2007), including risk transfer (which includes pooling risk), risk retention (i.e., creating a buffer, typically by saving resources), risk avoidance (i.e., finding ways to steer clear of high risk options in favor of low risk ones), and, finally, true risk reduction (i.e., taking steps to reduce the severity of negative events, including getting vaccinated, wearing seatbelts, and so on).

If need-based transfers are about risk-pooling, then why not call them simply “risk pooling”? That was our own inclination until a pivotal conversation we had a few years ago with Dan Hruschka, an ASU anthropologist and a friend of the Human Generosity Project. He pointed out that risk-pooling was an outcome, not an act of generosity or resource transfer in and of itself. ‘Need-based transfer,’ on the other hand, is a term that describes the underlying algorithm, the decision rule that individuals use. Need-based transfers are resource transfers that are conditional on the need of the recipient. Need-based transfers are a particularly effective algorithm for pooling risk, but other rules (such as account-keeping reciprocity) also provide some risk pooling benefits. Our computer simulations have shown that account-keeping rules lead to more risk pooling than no transfers, but that need-based transfers are even better, leading to more risk pooling and better survival than account-keeping (Aktipis et al. in press).

If need-based transfers pool risk more effectively than account-keeping, why do the two patterns coexist? Why, for example, do Maasai have not only osotua relationships, but also the notion of debt? The answer lies in whether the need of the recipient arises predictably or unpredictably. When needs are predictable, people can make plans for having them met, perhaps by agreeing to exchange favors. For a good example, let’s return to the world of our Malpai ranchers. As mentioned above, Malpai ranchers engage in need-based transfers when their neighbors experience unexpected needs – injuries, illnesses, deaths in the family, broken equipment, and so on. But other kinds of needs are quite predictable. For example, everyone needs to round up and brand their livestock, and everyone needs to take their livestock to market. For those kinds of predictable needs, the ranchers engage in account-keeping rather than need-based transfers. They arrange their schedules to complement each other and, when they help a fellow rancher at, say, branding time, it is understood that they expect the same favor in return. Ranchers who fail to repay their debts are quickly dropped from this system of “neighboring” (Cronk 2015).

Given that need-based transfers do not need to repaid if the donor is never himself in need, it is inevitable that some individuals will, in the long run, pay a net cost rather than receive a net benefit. How, then, could it be adaptive to help others if you don’t have a net positive return? It is important to remember that selection favors not only the maximization of expected returns but also the avoidance of catastrophic losses. An analogy with the insurance industry might help. When you pay your insurance premiums, you do not hope to one day recoup them by filing a claim. After all, if you file a claim, that means something bad has happened – an accident, a fire, and so on. What you hope is that all your premiums end up being a complete waste of money. That would mean you had a very lucky, trouble-free life. But, given that life is unpredictable and that you are prudent, you go ahead and buy insurance and pay your premiums.

The example of the insurance industry demonstrates that it is possible to have systems that combine aspects of need-based transfers and account-keeping. What makes it possible for the insurance industry to create one type of hybrid system is its ability to accumulate actuarial data. While the risks for any one individual remain unpredictable, large data sets make risk predictable, on average, for large classes of individuals. That aggregate predictability then allows insurance companies to set their rates at appropriate levels. It may also be possible to have hybrid systems on smaller scales. For example, reputations may matter not only in account-keeping systems but also with need-based transfers: Someone who has previously received help but who then fails to give to someone else in need is someone whose future needs may well go unmet.

Failing to give to those in need is one of two ways to cheat in a need-based transfer system. The other is to feign need. This contrasts with account-keeping systems, where cheating is impossible to hide and has immediate real-world consequences: people who do not repay their debts do not receive any more loans. In need-based transfer systems, in contrast, it may be quite easy for people to cheat if it is difficult for others to assess either their needs or their ability to help. Furthermore, the practical consequences of such behavior might be minimal. If one elicits aid from a risk-pooling partner when one is not really in need, the partner may be marginally less able to provide aid at some future time when one is truly in need, but the aid received might also enable one to weather that future need without any outside help. If one fails to give to one’s genuinely needy risk-pooling partner even though one is able to do so, the needy partner may be unavailable to help in the future, but chances are that he or she was only one of several risk-pooling partners, anyway, and the wealth thus retained may also make it easier to avoid becoming needy in the future.

If cheating is a big enough problem, a system of need-based transfers, like any cooperative system, will collapse. How do people prevent that from happening? We have identified a couple of possibilities. In some circumstances, cheating is made difficult by the nature of the resource in question. Among Maasai and other pastoralists, for example, livestock is the main resource, and, to put it plainly, it is difficult to hide a cow. Among Hadza and other foragers, big game is difficult to hide. Another possibility, which we have examined in a commentary to be published soon in Religion, Brain, and Behavior, is that need-based transfer systems are often imbued with a sense of sacredness that implies a threat of supernatural punishment for anyone who cheats (Cronk and Aktipis, in press).

We are exploring the issue of cheating through laboratory experiments. Our preliminary findings indicate that, in a standard test of cheater detection abilities called the Wason Selection Task (Cosmides 1988), people are quite good at identifying cheaters in need-based transfers, particularly those who ask when they are not actually in need (Chang et al. 2015). This may help explain a recent finding in political science that people in both the US and Denmark support welfare payments to people who find themselves in need through no fault of their own while opposing such payments to people perceived as lazy (Petersen 2012). In short, those who receive help without actually being in need are perceived as cheaters regardless of whether the help is provided by the government or a friend.

Like Malpai ranchers, we all grapple with forces much larger than ourselves everyday. The uncertainties we face in coming decades, from climate change to infectious disease to challenges of new technologies make us as individuals, and as a society, more vulnerable than perhaps we realize. Human societies around the world use need-based transfers to enhance resilience to challenges and environmental volatility. As we face new global challenges in future decades, need-based transfer systems may offer us much to learn from. The Human Generosity Project team is working with policy makers and disaster recovery experts to explore the viability of need-based transfer strategies for enhancing social and ecological resilience. From water management in the Phoenix metropolitan area to disaster recovery in remote villages, need-based transfers are an ancient human solution that can offer novel strategies for handling the challenges and uncertainties of the future.

Aktipis, Athena, Rolando de Aguiar, Anna Flaherty, Padmini Iyer, Dennis Sonkoi, and Lee Cronk. In press. Cooperation in an uncertain world: For the Maasai of East Africa need-based transfers outperform account keeping in volatile environments. Human Ecology.

Bliege Bird, R. L, Bird, D. W., Kushnick, G. & Smith, E. A. 2002. Risk and reciprocity in Meriam food sharing. Evolution and Human Behavior 23:297–321.

Burnham, T. C., and D. D. P. Johnson. 2005. The biological and evolutionary logic of human cooperation. Analyse und Kritik 27:113-135.

Chang, Andy, Lee Cronk, and C. Athena Aktipis. 2015. Cheater detection in need-based transfers systems. Human Behavior and Evolution Society, Columbia, Missouri.

Cronk, Lee. 2007. The influence of cultural framing on play in the trust game: A Maasai example. Evolution and Human Behavior 28:352-358.

Cronk, Lee. 2015. “Neighboring”: a preliminary look at generosity and mutual aid among ranchers in the American Southwest (http://humangenerosity.org).

Cronk, Lee, and C. Athena Aktipis. In press. Sacredness as an implied threat of supernatural punishment: The case of need-based transfers. Religion, Brain, and Behavior.

Cronk, Lee, and Beth L. Leech. 2013. Meeting at Grand Central: Understanding the Social and Evolutionary Roots of Cooperation. Princeton, NJ: Princeton University Press.

Dorfman, M. S. 2007. Introduction to Risk Management and Insurance. Upper Saddle River, NJ: Prentice Hall.

Fiske, Alan P. 1991. Structures of Social Life: The Four Elementary Forms of Human Relations. New York: Free Press.

Gintis, Herbert. 2000. Strong reciprocity and human sociality. Journal of Theoretical Biology 206:169-179.

Petersen, M.B. 2012. Social welfare as small‐scale help: evolutionary psychology and the deservingness heuristic. American Journal of Political Science 56(1):1-16.

Sahlins, Marshall. 1965. On the sociology of primitive exchange. In The Relevance of Models for Social Anthropology, edited by M. Banton. London: Tavistock. Reprinted in Stone Age Economics (1972, Transaction).





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