Search Results

Synergy is where the interactions of a group of individuals becomes more than the sum of their parts. This chapter reviews how, through the use of social communication, foraging animals can increase their rate of finding food. This chapter discusses how mechanisms such as pheromone trails, dancing, and other signals act to increase group, and thus individual success. It also discusses how social dilemmas can arise where costly signalling can be exploited by non-signallers. It shows that under a range of conditions, specifically when group success increases more than linearly with group size, co-operative signalling can evolve without kin selection or recipricocity. This study serves to emphasise the importance in linking mechanism with function when studying collective behaviour of animals.

This chapter studies what happened at the Council, and the consequent sweeping away of the old structure. Melissa Jo Wilde invokes a theory of collective behavior to explain the astonishing events. The tradition of collective behavior theory and research is impressed by the frequently observed phenomenon of individuals merging into a group experience that is more powerful than the sum of the individual experiences. French sociologist Emile Durkheim suggested that the “effervescence” that affected the group seemed to be something that existed apart from the group. The chapter details the various explanations for the phenomenon of collective effervescence. One of the reasons for the sudden and dramatic revolution was that the resources available to support the old structures were not very strong. The wineskins were fragile and leaking already. Since the council, a large numbers of Catholics have been able to rationalize the apparent conflict between their Catholic allegiance and their dissent from Catholic sexual teaching.

Many cognitive and biological scientists have defended claims about distributed cognition, but they have been too liberal in their ascriptions of mental states. This chapter returns to the ten cases discussed in Chapter 1, and provides a taxonomy that makes it possible to situate various kinds of collective behavior within a macrocognitive framework. It is argued that only a few of these ten cases should be seen as genuine cases of macrocognition; but it is also argued that there are some kinds of collective behavior that are proper targets of cognitive scientific research. Finally, the possibility of collective belief and collective responsibility are discussed, and it is suggested that few existing groups are likely to be believers in the fullest sense of the term.

The chapter creates a theory of group-social facts and social institutions relying on the we-mode approach and the notion of collective “pattern-governed” behavior. The central notion in this account is we-mode collective acceptance. The account of this chapter is applied to social organizations and compared with John Searle’s recent theory of “making the social world”.

From neurons to insects to societies, across biology we see impressive feats of collective information processing. What strategies do these systems use to perform useful computations? Moving toward an answer to this question, this chapter focuses on common challenges in inferring models of complicated distributed systems and how the perspective of information theory and statistical physics is useful for understanding collective behavior.

This chapter discusses how models, combined with modern data sources and statistical methods, can be used to test different hypotheses about the causes of migration. It presents mathematical formulations for migration and discusses the ecological mechanisms that could spontaneously have given rise to migration-like patterns of space use from the interaction within and between groups of animals and their environment. This highlights that migration is best seen as lying on a continuum from sedentary to nomadic movement patterns and not as a clearly distinct movement behaviour. Given the multitude of potential processes leading to migration, and the constraints imposed by data collection methods, it may be difficult to observe and identify the original cause. With this caveat in mind, the use of inferential methods to detect, quantify, and identify the underlying mechanisms of migration is discussed, and the links between models, data, and inference are illustrated using three case studies.

The purpose of this chapter is to develop the link between collective gatherings and collective behavior as well as between socially shared beliefs and collective emotions. Demonstrations and rituals could be conceived of as experiences of collective flow in which shared emotions and identity fusion emerge. When collective behavior is coordinated, identity fusion with the group substantially increases. Empirical evidence supports Durkheim’s ideas that emotional communion resulting from interplay of participants emotions is at the heart of social rituals. Together, collective gatherings reinforce personal affects, social integration, and social beliefs, although these effects are stronger in participants experiencing higher emotional communion and fusion of identity with the group. Moreover, a high level of emotional communion and fusion of identity in demonstrations enhanced perceived collective emotions or emotional climate as well as provoked an increase in agreement with positive shared social beliefs.

This book seeks to understand not only the perpetrators of genocide but also other aspects of human behavior during the Holocaust. It explores the continuing and dynamic interaction between cognition and attitude on the one hand, and situation on the other, and rejects the notion that either can be seen as an “unmoved mover” of human behavior. Gratuitous cruelty is understood not only as a reflection of initial attitude (of hatred and contempt for the victim) but also as the product of an escalating process of harm-doing and devaluation of the victim, in which people are changed by what they do. Through the concept of “pluralistic ignorance”, it is argued that the attitudes of individuals within a group cannot necessarily be inferred from collective behavior and conformity to a perceived group norm. In addition, the book discusses the strong tendency of many to see social psychological explanations as deterministic and individually exonerating. The contributions of social psychology that help us understand how human beliefs are formed and behavior shaped must not be ignored.

This chapter describes an incident that occurred on July 15, 1927 in Vienna, Austria, to set the stage for a discussion of the concept of “the mass”. On this day, a protest march organized by workers escalated into violence when demonstrators were struck down by the police. When calm was restored, eighty-five civilians and four police officers had been killed, and more than one thousand people were injured. The fifteenth of July 1927 saw the breakdown of the democratic forms that had until then contained the political passions of Austria's postimperial society. From then on, the upper classes would associate the workers' idea of a good society with the raging masses or the Bolshevik revolution, and these masses would see, in the burghers' idea of a good society, the flashing muzzle of a gun.

While academics are apt to seek the development of theoretical explanations for social movements, activists are more concerned with learning practical lessons about their movements in order to further their goals. Activist theorizing happens within all social movements, but academics have tended to focus exclusively on reformist, mainstream movements. There have been impressive contributions by sociological theorists of movements, but activists remain frustrated and indifferent to the poor attempts to theorize about revolutionary or anti-authoritarian movements, such as anarchism. Consequently, the established theoretical explanations for movements—including relative deprivation, resource mobilization, frame alignment, and dynamics of contention—are of mixed relevance to anarchist movements. This chapter briefly introduces these assorted theories and applies to anarchist movements. Some of these theories address crucial concerns, like strategy, timing, scale, and risks of movements. More importance will be placed upon other key interpretations to be introduced later in the text (i.e., political opportunity, new social movements, and social capital theories). An appropriate orientation is taken toward developing “better theories”: conserving and improving what exists (of both American and European scholarly origin) that is good, and building better theories from currently un-addressed concerns. This chapter also explores what is the utility of social movement theory for anarchist movements themselves.

This chapter defines the different terms and processes that are the main themes of the book. This chapter starts by explaining how perturbations increase uncertainty, which pushes individuals to update and gather information. In social animals, this information is shared through the social network, which is used to make a decision about staying or leaving the patch. Finally, this decision is not going to be made individually but rather based on decisions made by others. Perturbations may accumulate until surpassing a tipping point; then the first individuals may start to disperse and the rest copies this behaviour, which cascade as long as more individuals disperse. This autocatalytic process is termed runaway dispersal, which may result in nonlinear population dynamics, such as hysteresis, critical transitions, and transient phenomena. These dynamics should occur at the local level (e.g. patch collapse) and metapopulation level (e.g. extinction–colonization turnover).

Medical students have to cope in stressful environments during training and later in their career. Emotional intelligence (EI) is useful in helping students and doctors cope, because of enhanced ability to manage stress. Yet conventional models of EI are limited in that they frame EI as an internal, static, and measurable trait. Such models assume a simplistic view of stress and fail to consider the importance of context. We have developed an alternative model that reconfigures EI as a distributed, dynamic phenomenon and an emergent property of a complex system. Our model of distributed EI may offer a valuable resource for learning how to cope in stressful settings because it takes account of the unique, global features of a group context, such as group atmosphere or shared affect. Learning how to access and respond to this shared affect, the intelligent part of collective emotional behavior, may ultimately govern how stressful encounters are managed. Helping students develop sensitivity to context is the key to distributed EI, and the work presented here will be useful for medical students, doctors, and learning facilitators. We present empirical evidence for the emergence of distributed EI in a problem-based learning group (PBL) during a stressful interaction, discuss theoretical implications of distributed EI, and offer suggestions on how small group facilitators might work within a collective framework to help students manage stressful environments.

This chapter discusses some of the most engaging natural phenomena, those in which highly structured collective behavior emerges over time from the interaction of simple subsystems. Emergence is generally understood to be a process that leads to the appearance of structure not directly described by the defining constraints and instantaneous forces which control a system. Over time “something new” appears at scales not directly specified by the equations of motion. An emergent feature also cannot be explicitly represented in the initial and boundary conditions. A feature emerges when the underlying system puts some effort into its creation. These observations form an intuitive definition of emergence. For it to be useful, however, one must specify what the “something” is and in what manner it is “new.” Otherwise, the notion has little or no content, since almost any time-dependent system would exhibit emergent features.

This chapter begins by asking why social movement scholars have paid so little attention to The Civil Sphere, given the centrality Alexander attaches to social movements. It offers a judicious overview of Alexander’s understanding of this contested sociological subfield, including a discussion of his understanding of forms of collective behavior other than social movements. The chapter proceeds to question whether the cases used by Alexander—the civil rights movement and the women’s movement—are typical or atypical. It also ponders where “distasteful” social movements fit into the scheme. This leads to a critical assessment of Alexander’s theoretical approach, given that his cultural sociology is obviously grounded in the “cultural turn” in the discipline, an approach that does not seem entirely convincing, the chapter argues.