Why conform to social norms

This does not mean, however, that external sanctions never play a role in compliance: for example, in the initial development of a norm sanctions may indeed play an important role. Yet, once a norm is established, there are several mechanisms that may account for conformity. Finally, the view that one conforms only because of the threat of negative sanctions does not distinguish norm-abiding behavior from an obsession or an entrenched habit; nor does that view distinguish social norms from hypothetical imperatives enforced by sanctions such as the rule that prohibits naked sunbathing on public beaches.

In these cases avoidance of the sanctions associated with transgressions constitutes a decisive reason to conform, independently of what others do. In fact, in the traditional rational choice perspective, the only expectations that matter are those about the sanctions that follow compliance or non-compliance. In those frameworks, beliefs about how other people will act—as opposed to what they expect us to do—are not a relevant explanatory variable: however, this leads to predictions about norm compliance that often run counter to empirical evidence.

The traditional rational choice model of compliance depicts the individual as facing a decision problem in isolation: if there are sanctions for non-compliance, the individual will calculate the benefit of transgression against the cost of norm compliance, and eventually choose so as to maximize her expected utility. Individuals, however, seldom choose in isolation: they know the outcome of their choice will depend on the actions and beliefs of other individuals.

Game theory provides a formal framework for modeling strategic interactions. Thomas Schelling , David Lewis , Edna Ullmann-Margalit , Robert Sugden and, more recently, Peyton Young , Cristina Bicchieri , and Peter Vanderschraaf have proposed a game-theoretic account according to which a norm is broadly defined as an equilibrium of a strategic interaction.

Characterizing social norms as equilibria has the advantage of emphasizing the role that expectations play in upholding norms. On the other hand, this interpretation of social norms does not prima facie explain why people prefer to conform if they expect others to conform. Take for example conventions such as putting the fork to the left of the plate, adopting a dress code, or using a particular sign language. In all these cases, my choice to follow a certain rule is conditional upon expecting most other people to follow it.

Once my expectation is met, I have every reason to adopt the rule in question. In fact, if I do not use the sign language everybody else uses, I will not be able to communicate. It is in my immediate interest to follow the convention, since my main goal is to coordinate with other people. This is the reason why David Lewis models conventions as equilibria of coordination games.

Such games have multiple equilibria, but once one of them has been established, players will have every incentive to keep playing it as any deviation will be costly.

Take instead a norm of cooperation. In this case, the expectation that almost everyone abides by it may not be sufficient to induce compliance. If everyone is expected to cooperate one may be tempted, if unmonitored, to behave in the opposite way.

The point is that conforming to social norms , as opposed to conventions, is almost never in the immediate interest of the individual. In such games the unique Nash equilibrium represents a suboptimal outcome. It should be stressed that—whereas a convention is one among several equilibria of a coordination game—a social norm can never be an equilibrium of a mixed-motive game.

However, Bicchieri has argued that when a norm exists it transforms the original mixed-motive game into a coordination one. Clearly the only Nash equilibrium is to defect D , in which case both players get T,T , a suboptimal outcome. Suppose, however, that society has developed a norm of cooperation; that is, whenever a social dilemma occurs, it is commonly understood that the parties should privilege a cooperative attitude.

Thus there are two equilibria: if both players follow the cooperative norm they will play an optimal equilibrium and get B,B , whereas if they both choose to defect they will get the suboptimal outcome S,S. More specifically, if a player knows that a cooperative norm exists and has the right kind of expectations, then she will have a preference to conform to the norm in a situation in which she can choose to cooperate or to defect. To understand why, let us look more closely to the preferences and expectations that underlie the conditional choice to conform to a social norm.

Note that universal compliance is not usually needed for a norm to exist. However, how much deviance is socially tolerable will depend on the norm in question. Group norms and well-entrenched social norms will typically be followed by almost all members of a group or population, whereas greater deviance is usually accepted when norms are new or they are not deemed to be socially important.

What matters to conformity is that an individual believes that her threshold has been reached or surpassed. For a critical assessment of the above definition of norm-driven preferences, see Hausman Brennan et al. Norms are clusters of normative attitudes in a group, combined with the knowledge that such a cluster of attitudes exists.

Condition i is meant to reflect genuine first personal normative commitments, attitudes or beliefs. Condition ii is meant to capture those cases where individuals know that a large part of their group also shares in those attitudes. Putting conditions i and ii together offers a picture that the authors argue allows for explanatory work to be done on a social-level normative concept while remaining grounded in individual-level attitudes.

Consider again the new coordination game of Figure 1 : for players to obey the norm, and thus choose C, it must be the case that each expects the other to follow it.

When a norm exists, however, players also believe that others believe they should obey the norm, and may even punish them if they do not. We prefer to comply with the norm as we have certain expectations. Suppose the player knows a norm of cooperation exists and is generally followed, but she is uncertain as to whether the opponent is a norm-follower. In this case the player is facing the following situation Figure 2.

According to Bicchieri, conditional preferences imply that having a reason to be fair, reciprocate or cooperate in a given situation does not entail having any general motive or disposition to be fair, reciprocate or cooperate as such. Having conditional preferences means that one may follow a norm in the presence of the relevant expectations, but disregard it in its absence.

Whether a norm is followed at a given time depends on the actual proportion of followers, on the expectations of conditional followers about such proportion, and on the combination of individual thresholds.

As an example, consider a community that abides by strict norms of honesty. A person who, upon entering the community, systematically violates these norms will certainly be met with hostility, if not utterly excluded from the group.

But suppose that a large group of thieves makes its way into this community. In due time, people would cease to expect honesty on the part of others, and would find no reason to be honest themselves in a world overtaken by crime. Such a reconstruction is meant to capture some essential features of norm-driven behavior; also, this analysis helps us distinguish social norms from other constructs such as conventions or personal norms. A limit of this account, however, is that it does not indicate how such equilibria are attained or, in other terms, how expectations become self-fulfilling.

While neoclassical economics and game theory traditionally conceived of institutions as exogenous constraints, research in political economy has generated new insights into the study of endogenous institutions. Some alternative accounts have helped reconcile insights about norm-driven behavior with instrumental rationality Elster b.

In turn, experimental findings have inspired the formulation of a wide range of models aiming to rationalize the behavior observed in the lab Camerer ; Dhami These frameworks can explain a good wealth of evidence on preferences for equitable income distributions; they cannot however account for conditional preferences like those reflecting principles of reciprocity e.

As noted above, the approach to social norms taken by philosophically-inclined scholars has emphasized the importance of conditional preferences in supporting social norms. These theories presuppose that players are hardwired with a notion of fair or kind behavior, as exogenously defined by the theorist. Since they implicitly assume that all players have internalized a unique—exogenous—normative standpoint as reflected in some notion of fairness or kindness , these theories do not explicitly model normative expectations.

That said, we stress that social preferences should not be conflated with social norms. Social preferences capture stable dispositions toward an exogenously defined principle of conduct Binmore By contrast, social norms are better studied as group-specific solutions to strategic problems Sugden ; Bicchieri ; Young b.

Accounting for endogenous expectations is therefore key to a full understanding of social norms. Relatedly, Guala offers a game-theoretic account of institutions, arguing that institutions are sets of rules in equilibrium. From the first account, he captures the idea that institutions create rules that help to guide our behaviors and reduce uncertainty.

With rules in place, we more or less know what to do, even in new situations. From the second, he captures the idea that institutions are solutions to coordination problems that arise from our normal interactions.

The institutions give us reasons to follow them. The function of the rules, then, is to point to actions that promote coordination and cooperation. Because of the equilibrium nature of the rules, each individual has an incentive to choose those actions, provided others do too.

Guala relies on a correlated equilibrium concept to unite the rules and equilibria accounts. On this picture, an institution is simply a correlated equilibrium in a game, where other correlated equilibria would have been possible.

In what follows we focus on lab experiments that identify social norms by explicitly measuring both empirical and normative expectations. Xiao and Bicchieri designed an experiment to investigate the impact on trust games of two potentially applicable—but conflicting—principles of conduct, namely, equality and reciprocity.

Note that the former can be broadly defined as a rule that recommends minimizing payoff differences, whereas the latter recommends taking a similar action as others regardless of payoff considerations. The experimental design involved two trust game variants: in the first one, players started with equal endowments; in the second one, the investor was endowed with twice the money that the trustee was given.

In both cases, the investor could choose to transfer a preset amount of money to the trustee or keep it all. However, in the asymmetry treatment empirical beliefs and normative expectations conflicted: this highlights that, when there is ambiguity as to which principle of conduct is in place, each subject will support the rule of behavior that favors her most. Reuben and Riedl examine the enforcement of norms of contribution to public goods in homogeneous and heterogeneous groups, such as groups whose members vary in their endowment, contribution capacity, or marginal benefits.

By contrast, with punishment, contributions were consistent with the prescriptions of the efficiency rule in a significant subset of groups irrespective of the type of group heterogeneity ; in other groups, contributions were consistent with relative contribution rules. These results suggest that even in heterogeneous groups individuals can successfully enforce a contribution norm. Most notably, survey data involving third parties confirmed well-defined yet conflicting normative views about the aforementioned contribution rules; in other words, both efficiency and relative contribution rules are normatively appealing, and are indeed potential candidates for emerging contribution norms in different groups.

Bicchieri and Chavez designed an experiment to investigate norm compliance in ultimatum games. Further, the experimenters had subjects play three instances of the above ultimatum game under different information conditions. Moreover, the frequency of Coin choices was highest in the public information condition, where such option was common knowledge and its outcome transparent: this shows that there proposers followed the rule of behavior that favored them most, and that such a rule was effectively a social norm.

In a subsequent study, Chavez and Bicchieri measured empirical and normative expectations as well as behavior of third parties who were given the opportunity to add to or deduct from the payoffs of subjects who had participated in an ultimatum game.

Third parties tended to reward subjects involved in equal allocations and to compensate victims of unfair allocations rather than punish unfair behavior ; on the other hand, third parties were willing to punish when compensation was not an available option.

The experimental results further show that third parties shared a notion of fairness as indicated by their normative expectations , and that such notion was sensitive to contextual differences.

Krupka and Weber introduced an interesting procedure for identifying social norms by means of pre-play coordination games. In brief, using alternative between-subjects variants of the dictator game, Krupka and Weber had participants assess the extent to which different actions were collectively perceived as socially appropriate: subjects providing these ratings effectively faced a coordination game, as they were incentivized to match the modal response given by others in the same situation such a pre-play coordination game was intended to verify the presence of shared normative expectations.

In short, Schram and Charness had participants in dictator games receive advice from a group of third parties. Bicchieri and Xiao designed an experiment to investigate what happens when empirical and normative expectations conflict.

To that end, participants in a dictator game were exposed to different pieces of information. Other groups were given both descriptive and normative information. This suggests that if people recognize that others are breaching the norm, then they will no longer feel compelled to follow the relevant rule of behavior themselves. To conclude, the studies surveyed here provide evidence of the role played by expectations in affecting behavior in a variety of social dilemmas.

In this regard, we note that in contrast to the vast literature on empirical beliefs, the number of lab studies that directly measure normative expectations is relatively limited: more research is clearly needed to investigate the interplay of empirical and normative information about applicable rules of behavior.

Thus far we have examined accounts of social norms that take for granted that a particular norm exists in a population.

However, for a full account of social norms, we must answer two questions related to the dynamics of norms. First, we must ask how a norm can emerge. Norms require a set of corresponding beliefs and expectations to support them, and so there must be an account of how these arise. Second, we must investigate the conditions under which a norm is stable under some competitive pressure from other norms. Sometimes, multiple candidate norms vie for dominance in a population.

Let us now turn to the question of norm emergence. Here we can see three classes of models: first, a purely biological approach, second, a more cognitive approach, and third, a structured interactions approach.

The most famous of the biological approaches to norms seek to explain cooperative behavior. The simplest models are kin selection models Hamilton These models seek to explain altruistic tendencies in animals by claiming that, as selection acts on genes, those genes have an incentive to promote the reproductive success of other identical sets of genes found in other animals. This mode of explanation can provide an account of why we see cooperative behaviors within families, but being gene-centered, cannot explain cooperative behavior toward strangers as strangers should not be sufficiently genetically related to merit altruistic behavior.

Reciprocal altruism, however, does not require an evolutionary argument; a simple model of learning in ongoing close-knit groups will do, and has the further advantage of explaining why certain types of cooperative behavior are more likely to emerge than others. All that matters in these models is that agents can properly identify other agents, such that they can maintain a record of their past behavior.

This allows for the possibility of reputations: people who have the reputation of being cooperative will be treated cooperatively, and those who have a reputation of being unfair will be treated unfairly. A variation on the idea of reciprocal altruism can be seen in Axelrod Axelrod noted that if the game is left like this, we find that the stable state is constant defection and no punishment. However, if we introduce a meta-norm—one that punishes people who fail to punish defectors—then we arrive at a stable norm in which there is no boldness, but very high levels of vengefulness.

It is under these conditions that we find a norm emerge and remain stable. That is, failure to retaliate against a defection must be seen as equivalent to a defection itself. What Axelrod does not analyze is whether there is some cost to being vigilant.

Namely, watching both defectors and non-punishers may have a cost that, though nominal, might encourage some to abandon vigilance once there has been no punishment for some time.

This model does not rely on a meta-norm of punishment; instead, it is purely driven by repeated interactions of conditional strategies. In their model, agents play anywhere from 1 to 30 rounds of a trust game for 1, iterations, relying on the 4 unconditional strategies, and the 16 conditional strategies that are standard for the trust game. After each round, agents update their strategies based on the replicator dynamic.

Most interestingly, however, the norm is not associated with a single strategy, but it is supported by several strategies behaving in similar ways.

The third prominent model of norm emergence comes from Brian Skyrms , and Jason Alexander In this approach, two different features are emphasized: relatively simple cognitive processes and structured interactions.

Though Skyrms occasionally uses the replicator dynamic, both tend to emphasize simpler mechanisms in an agent-based learning context. Alexander justifies the use of these simpler rules on the grounds that, rather than fully rational agents, we are cognitively limited beings who rely on fairly simple heuristics for our decision-making. Rules like imitation are extremely simple to follow. Best response requires a bit more cognitive sophistication, but is still simpler than a fully Bayesian model with unlimited memory and computational power.

These simpler learning rules provide the same function as the replicator dynamic: in between rounds of play, agents rely on their learning rule to decide what strategy to employ. Note that both Skyrms and Alexander tend to treat norms as single strategies. The largest contribution of this strain of modeling comes not from the assumption of boundedly rational agents, but rather the careful investigation of the effects of particular social structures on the equilibrium outcomes of various games.

Much of the previous literature on evolutionary games has focused on the assumptions of infinite populations of agents playing games against randomly-assigned partners. Skyrms and Alexander both rightly emphasize the importance of structured interaction. As it is difficult to uncover and represent real-world network structures, both tend to rely on examining different classes of networks that have different properties, and from there investigate the robustness of particular norms against these alternative network structures.

Alexander in particular has done a very careful study of the different classical network structures, where he examines lattices, small world networks, bounded degree networks, and dynamic networks for each game and learning rule he considers.

First, there is the interaction network, which represents the set of agents that any given agent can actively play a game with. To see why this is useful, we can imagine a case not too different from how we live, in which there is a fairly limited set of other people we may interact with, but thanks to a plethora of media options, we can see much more widely how others might act.

This kind of situation can only be represented by clearly separating the two networks. Thus, what makes the theory of norm emergence of Skyrms and Alexander so interesting is its enriching the set of idealizations that one must make in building a model. The addition of structured interaction and structured updates to a model of norm emergence can help make clear how certain kinds of norms tend to emerge in certain kinds of situation and not others, which is difficult or impossible to capture in random interaction models.

Now that we have examined norm emergence, we must examine what happens when a population is exposed to more than one social norm. In this instance, social norms must compete with each other for adherents. This lends itself to investigations about the competitive dynamics of norms over long time horizons.

In particular, we can investigate the features of norms and of their environments, such as the populations themselves, which help facilitate one norm becoming dominant over others, or becoming prone to elimination by its competitors. An evolutionary model provides a description of the conditions under which social norms may spread. One may think of several environments to start with.

A population can be represented as entirely homogeneous, in the sense that everybody is adopting the same type of behavior, or heterogeneous to various degrees. In the former case, it is important to know whether the commonly adopted behavior is stable against mutations. An evolutionarily stable strategy is a refinement of the Nash equilibrium in game theory. Unlike standard Nash equilibria, evolutionarily stable strategies must either be strict equilibria , or have an advantage when playing against mutant strategies.

Since strict equilibria are always superior to any unilateral deviations, and the second condition requires that the ESS have an advantage in playing against mutants, the strategy will remain resistant to any mutant invasion.

This is a difficult criterion to meet, however. Tit-For-Tat is merely an evolutionarily neutral strategy relative to these others. If we only consider strategies that are defection-oriented, then Tit-For-Tat is an ESS, since it will do better against itself, and no worse than defection strategies when paired with them. Each social role carries expected behaviors called norms. Social norms are the unwritten rules of beliefs, attitudes, and behaviors that are considered acceptable in a particular social group or culture.

Norms provide us with an expected idea of how to behave, and function to provide order and predictability in society. For example, we expect students to arrive to a lesson on time and complete their work. The idea of norms provides a key to understanding social influence in general and conformity in particular. Social norms are the accepted standards of behavior of social groups.

These groups range from friendship and workgroups to nation-states. There are norms defining appropriate behavior for every social group. For example, students, neighbors and patients in a hospital are all aware of the norms governing behavior. And as the individual moves from one group to another, their behavior changes accordingly. Norms provide order in society. In the U.

Federal court system, many important cases go through three-judge panels. The majority opinion of these panels carries the day, meaning that having a majority is crucial for one side or another to get the rulings they want. But a study of the judicial behavior of the District of Columbia Circuit came to a surprising conclusion: A panel of three GOP-appointed judges was actually considerably more likely to make a conservative ruling than a panel of two GOP appointees and one Democratic appointee.

Just one Democratic dissenter appeared to make the difference; the dissenter apparently swayed their colleagues, demonstrating how viewpoint diversity has the power to alter the conclusions of a group.

This court study is among many cited by legal scholar Cass Sunstein in his new book Conformity: The Power of Social Influences , which delves deeply into how and why individuals often follow the opinions and behaviors of groups they belong to. On the contrary, he reiterates numerous circumstances when society can benefit from it. For instance, Sunstein notes how conformity helped encourage public smoking laws.

One study found that when public smoking bans were enacted in three California cities, compliance was high, and the cities received few reports of violations. And if most people think it is wrong to smoke in public places, would-be smokers are less likely to smoke, in part because they do not want to be criticized or reprimanded.

But conformity also carries with it the power to make human beings ignore their own consciences, sometimes to the point of committing atrocities. Milgram found that all of the participants were willing to shock the confederate at volts, and two-thirds continued to administer shocks at the very highest level of voltage.

The participants were simply willing to trust the instructor that what they were doing was okay. In order to understand how conformity works—from fairly banal examples such as public smoking bans all the way up to atrocities committed during World War II—Sunstein breaks it down into its component parts:.

Signals from in-groups—people you like, trust, or admire—are far more valuable than information signals from out-groups. Reputational signals: We may have private qualms about a point of view or given course of action, but because we want to remain in the good graces of our social grouping, we suppress our dissent and eventually fall in line.

To demonstrate how a cascade can work, he cites a study by sociologist Duncan Watts, in which study participants were asked to rank a group of seventy-two songs from best to worst.