Hostile and aggressive behaviors, as seen in research, tend to be strongly imitated

Observational Learning of Cognitions and Behaviors

Previously it was thought that observational learning of behaviors, as described above, by itself accounted for the relation between viewing of violence on TV and its subsequent enactment by the viewer. It has been demonstrated that by frequent observation of violence children also learn cognitions that support the use of violence in interpersonal actions; it is these cognitions that often mediate or provide the link between observation and later behavior (Berkowitz, 1984). Not only do young viewers adopt specific behaviors modeled by others but they also tend to adopt evaluative standards used by those models. By observing violence in the media, children learn scripts for complex aggressive behaviors and at the same time adopt attitudes about the appropriateness of aggressive and violent behavior. The latter have been termed normative beliefs. Scripts are programs for behavior that lay out a sequence of events that the individual believes is likely to happen and how one is to respond given what is appropriate and possible for a particular situation. Normative beliefs act as internal self-regulatory standards serving to filter out behaviors that are not acceptable. Both are acquired from culture via observational learning and modeling. Cognitive rehearsal of these scripts and normative beliefs occur whenever the child is exposed to a violent sequence on TV or fantasizes about a sequence previously observed. These reexposures and fantasy experiences serve as rehearsals of the violent sequence which are then more readily called up from memory and serve as guides to action. An individual who has previously learned mostly violent scripts and very few prosocial scripts, for example, will likely resort to the violent ones when faced with an ambiguous social interaction since they are better learned than the prosocial scripts and thus will be retrieved from memory more readily.

There are also at least five variables that are important in affecting the magnitude of the TV viewing–aggression relation mediated by cognitions. These are the child's intellectual achievement, social popularity, identification with TV characters, belief in the realism of violence shown on TV, and the amount of fantasizing about aggression in which the child engages. These variables are considered moderators of the relation. These and other moderators are discussed below.

1.12. CONCLUSION

Observers have long wondered whether sudden large shifts in prices, actions, and resource allocation in capital markets are caused by social contagion. Such phenomena include asset and security market booms and crashes; real investment booms and busts; takeover and financing waves (including boom/bust patterns in the design of securities, such as asset-backed securities); shifts in disclosure practices, such as the use of pro forma earnings disclosures; and financial market runs. Often the behaviors of relevant participants converge despite negative payoff externalities, suggesting that such patterns may be caused by contagious effects of psychological bias or by the failure of rational social learning to aggregate information efficiently.

We review here the causes and effects of contagion of thoughts and behaviors in capital markets among participants such as investors, managers, security analysts, advisors, and media commentators. We examine theory and evidence about how rational observational learning, agency problems, and psychological forces affect contagion in firms' investment, financing, and disclosure choices and in investors' trading decisions and the consequences of contagion for the pricing of real assets and securities. In addition to herding by managers or other agents, we consider how such agents exploit the readiness of investors to herd.

An externality problem is central to the theory of rational observational learning. Each individual maximizes his own payoff without regard to the effect of his choice on the information obtained by later decision makers by observing the individual's action choice and/or the payoff consequences of that choice. Over time, individuals act mainly based on the accumulated inventory of public information (perhaps including payoff information) generated by past actions. This delays or blocks the generation and revelation of further information.

Thus, in a range of economic settings, even if payoffs are independent and people are rational, decisions tend to quickly converge on mistaken action choices. In other words, the resulting cascade or herd is idiosyncratic. Owing to idiosyncrasy, rational individuals place only modest faith in the conventional action; the cascade or herd is easily dislodged (fragility). Furthermore, rational observational learning tends to cause simultaneity (delay followed by a sudden spasm of joint action), paradoxicality (increasing the availability of public information by various means can decrease welfare and decision accuracy), and path dependence (chance early events have big effects on ultimate outcomes).

Depending on the exact assumptions, information may be completely suppressed for a period (until a cascade is dislodged). Under other assumptions, no cascades form and asymptotically all uncertainty is resolved, but too slowly (relative to full aggregation of private signals). Information cascades require discrete, bounded, or gapped action space (or cognitive constraints); these conditions are highly plausible in many investment settings. Even when these conditions fail owing to noise, the growth in accuracy of the public information pool tends to be self-limiting because an individual who places heavy weight on the information derived from past actions puts little weight on his own signal, making his own action less informative to those who follow.

Markets have been praised as marvels of spontaneous information aggregation (Hayek, 1945). Indeed, we see that rational price setting in perfect markets encourages investors to use their private signals rather than imitating the trades of others, discouraging direct information cascades of trading. However, in settings with multiple dimensions of uncertainty, quasi-cascading behavior can occur in which individuals trade in opposition to their information signals.

Furthermore, transaction costs, minimum trade sizes, or psychological biases can prevent price from fully aggregating information. As a result, proper trading cascades can form, including cascades in participation versus nonparticipation in markets. Even without frictions or biases, information cascades (and other sources of herd behavior) in investigation indirectly affect trading and the amount of information aggregated into market price. So, despite some arguments to the contrary, in several economic settings information cascades affect securities trading and prices.

Although inefficient behaviors can be locked in by noninformational factors (such as positive payoff externalities), the theories of rational observational learning, especially the information cascades theory, differ in their implication of fragility. Therefore, payoff externality models are helpful in explaining herds that seem stable and robust.48 Reputational models, for example, generate stable patterns of herding or dispersing through endogenously generated payoff externalities. Reputational models help explain when herding versus dispersing will occur and offer implications about the effect on the pressure to herd on the career status of managers.

We need new models of price setting in financial markets in which beliefs are not transmitted solely through price, in which ideas spread between neighbors in a social network and by means of electronic media. Furthermore, we need analysis that reflects the fact that the information conveyed is not necessarily a simple normally distributed signal, processed in some rational or quasi-rational fashion. Often what are conveyed are investment ideas or memes, and we need to understand how both isolated financial memes (e.g., “This stock is going to rise”) and full-fledged financial ideologies (such as “new era” theories and the value and growth ideologies) spread from person to person as a sort of social epidemic. Empirical testing will of course be crucial to the success of a research program based on thought contagion.

Such a program involves understanding the spread of particular financial memes viewed as an epidemic, studying the characteristics of financial memes that tend to promote their own replication, and assessing the characteristics of the environment that favor different kinds of memes. In other words, it involves studying what makes some financial memes better adapted than others. Even more ambitiously, it is important to understand why certain financial memes complement each other and how this leads to the cumulative evolution of financial ideologies that are well adapted in the sense that they are good at spreading themselves.

We have suggested that many of the puzzles and anomalies of capital markets can be understood by going beyond a focus on individual psychological biases and the way biased individuals interact through trading and market price. Instead, as Robert Shiller has proposed, we need to understand the social processes that lead to the spread of popular ideas. For dynamic phenomena such as bubbles and crashes, the concept of availability cascades is especially promising. We have offered some tentative speculative memetic explanations for such phenomena as the survival of invalid capital budgeting methods and money-losing active trading strategies, bubbles, hot IPOs, short-run fluctuations in the profitability of value versus growth strategies and frequencies of the value and growth ideologies, and long-run coexistence of these ideologies.

6.08.4.3 Common Learning Principles

Both the motor skills and problem solving models employ a common set of learning principles, based mainly on instrumental (or operant) and observational (or social) learning theories (Bandura, 1969; Skinner, 1938), to train new social skills. Modeling (demonstrating a skill in a role-play) is frequently employed to familiarize clients with the basic steps of targeted skills. Verbal reinforcement is generously used to encourage effort and to draw attention to particular component skills that were performed well in a role-play situation.

Shaping refers to the reinforcement of successive approximations to a goal. Social skills require the complex integration of a number of component skills. Typically, these skills are learned gradually over many role-plays and with much practice outside of the sessions. Therefore, in order to encourage clients to keep trying, and to recognize their progress in acquiring targeted component skills, behavior needs to be shaped gradually over time by providing ample reinforcement along the way.

Generalization is the ability to transfer a skill learned in one setting to another situation. In order for social skills training to improve social functioning, clients must be able to use the skills acquired in training sessions in real-life settings. Therefore, programming the generalization of skills to client's natural living environments is an integral part of social skills training. Some of the strategies employed to facilitate generalization include community trips for clients to practice skills on their own, homework assignments, and teaching significant others (e.g., family members, staff members) to prompt clients to use skills in appropriate situations.

Modeling

The second type of parenting behavior emphasized in the expectancy-value model is parental modeling. Parents' vocational and leisure pursuits can influence their children's choices through processes associated both with observational learning and with the desire to be like their parents (Bandura, 1997; Eccles, 1993). Although modeling is often cited as theoretically important for children's acquisition of attitudes and behaviors, the empirical support for role modeling is mixed. Some studies show a significant link between modeling and participation (e.g., Kahn et al., 2008), whereas others show no relation (e.g., Fredricks and Eccles, 2005).

There are several possible explanations for these mixed findings. First, in some of these studies, modeling and other parenting behaviors were included within the same regression-based analysis, and parent modeling may be a weak unique predictor relative to other behaviors (e.g., coactivity). Another possibility is that modeling may only be effective when a behavior or activity can be learned by simply watching someone. Modeling may have a weak influence on activities that are more cognitive in nature and require instruction, such as completing a math problem or reading a book. Furthermore, parents' engagement in these domains in the presence of their children is likely to vary. We have found that few parents play musical instruments themselves or have a music-related career (Simpkins et al., manuscript under review). Parents' engagement in other domains, like sports, may only influence children if they see their parent exercising or have knowledge of these activities.

Imitating Inferred Strategies

In addition to inferring the general goal underlying others' acts, children can also reproduce the rules or strategies that guide others' behaviors. This is a way that adults may commonly use observational learning; Studying the way a good speaker presents information can be as informative as the content of the talk. One type of abstract information that children learn through imitation is the temporal order of an action sequence (Subiaul et al., 2007a,b). Preschoolers who saw an adult press series of pictures in a particular order on a touch screen (like entering an ATM pin code) needed fewer trials to input the same sequence than did children who had to learn through trial and error. Importantly, the location of the pictures varied between each trial. This meant that the children had to learn the order in which to press the pictures, not the adult's motor movements.

Preschoolers also imitate the hierarchical organization that structures action (Flynn and Whiten, 2008; Whiten et al., 2006). In these tasks, children watched an adult assemble and use a series of keys to unlock a box and retrieve a reward. The adult either assembled and used one key before moving to the next key, or he completed one assembly step with all of the keys before moving to the next step. The children maintained the adult's hierarchical strategy when opening the box themselves; e.g., children who saw the adult take a stepwise approach also completed each step in turn.

Children also imitate abstract sorting rules from others' behaviors (Williamson et al., 2010). In one experiment, children saw an adult sort a set of objects into two piles based on their colors. Children were given a chance to sort the same objects and a second set of objects. The second set included different kinds and colors, and the adult never sorted them. This set was used to test whether children would generalize the sorting rule. Three control groups were used to pinpoint the critical elements of a demonstration for promoting sorting. In the most stringent control, the adult brought out the objects presorted by color, picked up each object, and returned each to its starting location. These behaviors were carefully matched to the experimental group, except the adult never sorted the objects.

The first finding from this experiment was that children who saw the adult's sorting behaviors were more likely to reproduce the color sorting strategy than were children in the control groups (see Figure 1(b)). Sorting behaviors were critical for eliciting imitation. Closely matched demonstrations that did not include sorting did not prompt children to imitate. A second finding was that children who saw the adult's sorting behaviors applied the color sorting rule to the second set of object, even though they were not shown what to do with those objects. This illustrates an important benefit of imitating abstract strategies and rules. Unlike specific behaviors on objects, rules are generalizable across materials and situations.

Theory and Mechanisms

The BASIC I.D. or multimodal framework rests on a broad social and cognitive learning theory (e.g., Bandura, 1977, 1986) because its tenets are open to verification or disproof. Instead of postulating putative unconscious forces, social learning theory rests on testable developmental factors (e.g., modeling, observational learning, the acquisition of expectancies, operant and respondent conditioning, and various self-regulatory mechanisms). It must be emphasized that while drawing on effective methods from any discipline, the multimodal therapist does not embrace divergent theories but remains consistently within social-cognitive learning theory. The virtues of technical eclecticism (Lazarus, 1967, 2005, 2008) over the dangers of theoretical integration have been emphasized in several publications (e.g., Lazarus, 1989, 1995; Lazarus and Beutler, 1993).

The major criticism of theoretical integration is that it inevitably tries to blend incompatible notions and only breeds confusion (see Beutler et al., 1995). The main claim is that by assessing clients across the BASIC I.D., one is less apt to overlook subtle but important problems that call for correction, and the overall problem identification process is significantly expedited.

Social Learning Theory

Social Learning Theory was popularized by Bandura (1986), and encompasses how observations in the social world impact behaviors and cognitions. Although classical and operant conditioning are still relevant, Bandura also proposed modeling, where an observer views a person's actions and their consequences. If that person is rewarded, the observer is more likely to mimic those actions. However, if the action is punished, the observer learns to expect negative consequences from that behavior. Modeling may take place immediately (direct imitation) or the consequences of the behavior are remembered later (observational learning) (Nelson, 2010). For example, premarital sex may be rewarded in some communities and punished in others; and by observing these consequences, members of these communities learn the expectations of acceptable sexual behavior. In fact, the belief that peers are also sexually active is a strong predictor of previous engagement in sexual activity (Christopher et al., 1993; see Sexual Debut). Thus, socialization, culture, and media contribute to the development of expectations of the consequences of behaviors and one does not need to experience reinforcement or punishment personally in order to be affected. Bandura (1977) proposed that after successfully performing a task, one experiences a sense of self-efficacy. In the sexual context, the affective experience and timing of first intercourse may be of particular importance, as it has a strong impact on sexual self-efficacy, which is positively correlated with healthy sexual adjustment in later life (Reissing et al., 2011, 2005).

Although heavily supported through empirical research, the primary criticisms of the social learning theory include that it assumes passivity in the nature of the observer who recieves rewards or punishments, that the theory does not explain why certain behaviors are rewarded or punished, and that it fails to explain why some individuals will not conform to social norms (Nelson, 2010). The following theories will address some of these concerns.

Interpersonal Violence

Two prominent forms of interpersonal violence are spouse abuse and homicide. Spouse abuse is rooted in the cultural and structural violence of patriarchy that create rigid gender roles and systematically privilege men over women and legitimate the use of violence as a means of disciplining one's spouse and demonstrating machismo. In most societies, men hold greater power than women, and members of both genders internalize values and hold to social roles that privilege men as the decision-makers. At the household level, many men believe they have dominion over the home and may regard challenges to their authority as a transgression that must be answered by violence. In grim testimony to the potency of observational learning, men's tendency to beat their spouse often increases significantly if the men themselves have grown up in families in which men beat their wives. In many war zones, rates of spouse abuse frequently rise as unemployed men, who have lost their role as providers, use spouse abuse as a means of venting frustration, reasserting control over their domain, and boosting their sense of power and manhood.

The diverse causes of homicide have been illuminated by studies of aggression, which includes both reactive and intentional violence with hostile intent. A distinction can be made between hostile aggression that is emotionally driven by anger, hatred, or fear and evoked without much thought, and instrumental aggression that is used by people to attain particular goals. Both forms of violence may be strongly influenced by cognition. For example, people who are angry tend to engage in higher levels of violence if the situation contains cues such as the sight of weapons that people usually associate with violence. Instrumental violence is influenced by how people perceive themselves in relation to their social environment. In a very poor, urban neighborhood, for example, materially deprived youth may use violence as a means of taking coveted items such as expensive clothes, thereby demonstrating their power and gaining respect for their prowess. To maintain power, individuals may be highly watchful for the slightest sign of disrespect, which they respond to with violence. In such contexts, respect is important and very much in the eye of the beholder.

Summary and Conclusion

This article has presented an overview of the definition, theoretical explanations, and individual as well as situational moderators of aggression as a form of social behavior that is defined by the intention to harm. Theories refer to affective and cognitive reactions to aggression-eliciting stimuli and the way in which they pave the way for aggressive responses. They explain how negative affect, caused by a range of adverse stimuli such as frustration, pain, or noise, triggers selective information processing that increases the probability of aggressive behavior. This information processing is influenced by an individual's learning history, comprising both direct reinforcement and observational learning, and draws on stored knowledge in the form of cognitive schemata, such as aggressive scripts. The General Aggression Model integrates the mechanisms proposed by different theories into a common framework.

The theoretical models also seek to explain differences between individuals and between situations in the likelihood of aggressive behavior. On the person side, aggressiveness has been identified as a trait, reflecting stable individual differences in the propensity to act aggressively and to interpret others' actions as an expression of hostile intent. Moreover, research has found a greater readiness to engage in physical aggression in males than in females, but little evidence of a gender difference in relational aggression. Among the situational variables, research has consistently shown that alcohol consumption, exposure to media violence, high temperatures and the availability of firearms lower the threshold for aggressive behavior. Finally, promising avenues for preventing aggression include anger management trainings, the presentation of nonaggressive behavioral models, and the situational elicitation of affective and cognitive states that are incompatible with anger.

The theoretical accounts presented in this chapter seek to explain aggression as a form of social behavior that is common in many spheres of everyday life. Their focus is not on offering a comprehensive understanding of severe acts of criminal violence that are rare and require additional theorizing from other fields. Even for everyday forms of aggression, psychological explanations can illuminate only part of the picture. Understanding aggressive behavior needs to be an interdisciplinary endeavor, bringing together theories, methods, and findings from as many different fields as possible, to create a knowledge base on which effective prevention measures may be built.

Mainstream Cognitive Theories