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Merton proposed middle range theories, not as ends in themselves, but as bases for a consolidation to explain broader phenomenon. More than a half century has passed since Merton's consolidation proposal and in that time a number of experimentally tested middle range theories have been developed. Certainly, the next step should be a consolidation. Yet, to our knowledge, no one has previously offered a consolidation of experimentally tested theories and applied it for explanation. This paper offers a consolidation of middle range theories formulated to explain the rise of the pristine state. Two theories of this consolidation, Status Characteristics Theory and Elementary Theory, form the core of what Analytic Sociologists have called a toolbox of theories. Our toolbox forms an integrated consolidation in two ways. First, the social structures modeled by the theories form a path-dependent process of increasing benefits gained by the elites of the structures. Second, the end conditions of each step of the process are the initial conditions of the next. Whereas the theories in our toolbox have previously been seen as applying exclusively to microstructures, we have encountered no difficulties in scaling them up to apply to macrostructures. While we hope the consolidation has validity in explaining the occurrence of pristine states, this paper's significance lies in its demonstration that today social theories can be consolidated and applied for explanation. [ABSTRACT FROM AUTHOR]

The paper offers a distinctive reading of Popper’s work, suggesting that his Logic of Scientific Discovery (LScD) might be re-interpreted in the light of his Open Society. Indeed, Popper can be interpreted as criticising certain aspects of his first book, and as a result improving upon them, in his second. It suggests translating what Popper says about ‘conventions’ into his later vocabulary of ‘social institutions’. Looking back, I believe that Popper never intended the language of conventions and decisions to be read individualistically. I remain unsure whether Popper was himself quite as clear about this as he could have been. My reading makes Popper a pioneer in the sociology of science. Scientific institutions are arenas of political power; but Popper did not discuss the structure and inter-relations of the social institutions of science, or offer a politics of science in the context of his methodology. What is missing from the skeletal sociology of LScD is the politics. We could put it in Popperian terms this way: scientific institutions are both open and closed. They are closed, firmly, to the inexpert, to the nonmembers; supposedly they are open to the qualified, provided the prerogatives of seniority and leadership are acknowledged. Despite these shortcomings, Popper’s critical and rational approach and his insistence on openness and intellectual honesty are still important today. [ABSTRACT FROM AUTHOR]

This paper exposes a theoretical approach proposal for the analysis of social inequalities through the notions of socialization and subjective experience, from a comprehensive sociology and Schutz's phenomenological perspective. The intention is to emphasize the subjective dimension in the phenomenon of inequality, which refers to the naturalization that occurs through the mental categories that we use to look at and build the social world, and that results in an aspect that strongly adds to structural conditioning of this problem. In particular, it is proposed to study this phenomenon in the context of high school, since it represents a particular period of life in which teenagers appropriate identity categories and in relation to the social order in which they operate. The results, from this approach, propose to rescue the role of the educational institution in the subjective incorporation of this problem, and, with it, address school practices and their objective effects on the lives of students. [ABSTRACT FROM AUTHOR]

This paper reflects on the dynamics of today's financial markets in the light of two concepts -- publics and multitudes -- which were developed by the sociologist Gabriel Tarde at the end of the 19th Century. Each of the concepts reveals a different way of structuring social links among individuals. We consider that Tarde's concepts let us: (1) stress the communicative dimension of today's financial markets, placing currents of opinion at the core of speculative activity in the creation and assignment of value to monetary flows and other financial instruments; (2) hypothesise that financial markets articulate the logic of 'publics' (or audiences). These markets are virtually, globally connected, spreading currents of opinion that link financial experts and ordinary folk. They also link the multitudes (giving rise to 'bubbles', key social-temporal moments, and e-valuations through community links among professional agents -- all features that can pave the way to a crisis). The paper's point of departure is a review of present theories on Market Sociology. It then delves into the contributions that the concepts of 'public' and 'multitude' make in shedding light on financial dynamics and hence on the Sociology of Finance. [ABSTRACT FROM AUTHOR]

Social networks influence health-related behavior, such as obesity and smoking. While researchers have studied social networks as a driver for diffusion of influences and behavior, it is less understood how the structure or topology of the network, in itself, impacts an individual's health behavior and wellness state. In this paper, we investigate whether the structure or topology of a social network offers additional insight and predictability on an individual's health and wellness. We develop a method called the Network-Driven health predictor (NetCARE) that leverages features representative of social network structure. Using a large longitudinal data set of students enrolled in the NetHealth study at the University of Notre Dame, we show that the NetCARE method improves the overall prediction performance over the baseline models—that use demographics and physical attributes—by 38%, 65%, 55%, and 54% for the wellness states—stress, happiness, positive attitude, and self-assessed health—considered in this paper. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present new theorisations of social structure in light of the new sociologies of the individual currently being developed in France. Although these sociologies are little known, they have significant value in rethinking today's society and sociology. Starting from a review of the concept and the main conceptions of social structure, I will focus on the most significant contributions of these new sociologies of the individual. To do this, on the one hand, it will be shown that the two classical traditions of social structure (institutional or cultural and as a class structure) are insufficient to explain today's society, in which the individual has become the main protagonist and key focus of sociology. On the other hand, in contrast with the old sociologies of the individual, which are centred on the micro level of social interaction, this paper analyses new structural constraints that limit the individual's action. The paper concludes with an invitation to develop these new sociologies at an individual scale. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present new theorisations of social structure in light of the new sociologies of the individual currently being developed in France. Although these sociologies are little known, they have significant value in rethinking today's society and sociology. Starting from a review of the concept and the main conceptions of social structure, I will focus on the most significant contributions of these new sociologies of the individual. To do this, on the one hand, it will be shown that the two classical traditions of social structure (institutional or cultural and as a class structure) are insufficient to explain today's society, in which the individual has become the main protagonist and key focus of sociology. On the other hand, in contrast with the old sociologies of the individual, which are centred on the micro level of social interaction, this paper analyses new structural constraints that limit the individual's action. The paper concludes with an invitation to develop these new sociologies at an individual scale. [ABSTRACT FROM AUTHOR]

This paper addresses the question of whether one can generate networks with a given global structure (defined by selected blockmodels, i.e., cohesive, core-periphery, hierarchical, and transitivity), considering only different types of triads. Two methods are used to generate networks: (i) the newly proposed method of relocating links; and (ii) the Monte Carlo Multi Chain algorithm implemented in the package in R. Most of the selected blockmodel types can be generated by considering all types of triads. The selection of only a subset of triads can improve the generated networks’ blockmodel structure. Yet, in the case of a hierarchical blockmodel without complete blocks on the diagonal, additional local structures are needed to achieve the desired global structure of generated networks. This shows that blockmodels can emerge based only on local processes that do not take attributes into account. [ABSTRACT FROM AUTHOR]

Size estimation is particularly important for populations whose members experience disproportionate health issues or pose elevated health risks to the ambient social structures in which they are embedded. Efforts to derive size estimates are often frustrated when the population is hidden or hard-to-reach in ways that preclude conventional survey strategies, as is the case when social stigma is associated with group membership or when group members are involved in illegal activities. This paper extends prior research on the problem of network population size estimation, building on established survey/sampling methodologies commonly used with hard-to-reach groups. Three novel one-step, network-based population size estimators are presented, for use in the context of uniform random sampling, respondent-driven sampling, and when networks exhibit significant clustering effects. We give provably sufficient conditions for the consistency of these estimators in large configuration networks. Simulation experiments across a wide range of synthetic network topologies validate the performance of the estimators, which also perform well on a real-world location-based social networking data set with significant clustering. Finally, the proposed schemes are extended to allow them to be used in settings where participant anonymity is required. Systematic experiments show favorable tradeoffs between anonymity guarantees and estimator performance. Taken together, we demonstrate that reasonable population size estimates are derived from anonymous respondent driven samples of 250-750 individuals, within ambient populations of 5,000-40,000. The method thus represents a novel and cost-effective means for health planners and those agencies concerned with health and disease surveillance to estimate the size of hidden populations. We discuss limitations and future work in the concluding section. [ABSTRACT FROM AUTHOR]

Micro-blogging systems have become one of the most important ways for information sharing. Network structure and users’ interactions such as forwarding behaviors have aroused considerable research attention, while mention, as a key feature in micro-blogging platforms which can improve the visibility of a message and direct it to a particular user beyond the underlying social structure, is seldom studied in previous works. In this paper, we empirically study the mention effect in information diffusion, using the dataset from a population-scale social media website. We find that users with high number of followers would receive much more mentions than others. We further investigate the effect of mention in information diffusion by examining the response probability with respect to the number of mentions in a message and observe a saturation at around 5 mentions. Furthermore, we find that the response probability is the highest when a reciprocal followship exists between users, and one is more likely to receive a target user’s response if they have similar social status. To illustrate these findings, we propose the response prediction task and formulate it as a binary classification problem. Extensive evaluation demonstrates the effectiveness of discovered factors. Our results have consequences for the understanding of human dynamics on the social network, and potential implications for viral marketing and public opinion monitoring. [ABSTRACT FROM AUTHOR]

This article aims to present some of the initial work of developing a social science grounded game theory-as a clear alternative to classical game theory. Two distinct independent initiatives in Sociology are presented: One, a systems approach, social systems game theory (SGT), and the other, Erving Goffman's interactionist approach (IGT). These approaches are presented and contrasted with classical theory. They focus on the social rules, norms, roles, role relationships, and institutional arrangements, which structure and regulate human behavior. While strategic judgment and instrumental rationality play an important part in the sociological approaches, they are not a universal or dominant modality of social action determination. Rule following is considered, generally speaking, more characteristic and more general. Sociological approaches, such as those outlined in this article provide a language and conceptual tools to more adequately and effectively than the classical theory describe, model, and analyze the diversity and complexity of human interaction conditions and processes: (1) complex cognitive rule based models of the interaction situation with which actors understand and analyze their situations; (2) value complex(es) with which actors operate, often with multiple values and norms applying in interaction situations; (3) action repertoires (rule complexes) with simple and complex action alternatives-plans, programs, established (sometimes highly elaborated) algorithms, and rituals; (4) a rule complex of action determination modalities for actors to generate and/or select actions in game situations; three action modalities are considered here; each modality consists of one or more procedures or algorithms for action determination: (I) following or implementing a rule or rule complex, norm, role, ritual, or social relation; (II) selecting or choosing among given or institutionalized alternatives according to a rule or principle; and (III) constructing or adopting one or more alternatives according to a value, guideline, or set of criteria. Such determinations are often carried out collectively. The paper identifies and illustrates in a concluding table several of the key differences between classical theory and the sociological approaches on a number of dimensions relating to human agency; social structure, norms, institutions, and cultural forms; patterns of game interaction and outcomes, the conditions of cooperation and conflict, game restructuring and transformation, and empirical relevance. Sociologically based game theory, such as the contributions outlined in this article suggest a language and conceptual tools to more adequately and effectively than the classical theory describe, model, and analyze the diversity, complexity, and dynamics of human interaction conditions and processes and, therefore, promises greater empirical relevance and scientific power. An Appendix provides an elaboration of SGT, concluding that one of SGT's major contributions is the rule based conceptualization of games as socially embedded with agents in social roles and role relationships and subject to cognitive-normative and agential regulation. SGT rules and rule complexes are based on contemporary developments relating to granular computing and Artificial Intelligence in general. [ABSTRACT FROM AUTHOR]

In this paper, I investigate a connection between a common characterisation of freedom and how uncertainty is managed in a Bayesian hierarchical model. To do this, I consider a distributed factorization of a group's optimization of free energy, in which each agent is attempting to align with the group and with its own model. I show how this can lead to equilibria for groups, defined by the capacity of the model being used, essentially how many different datasets it can handle. In particular, I show that there is a "sweet spot" in the capacity of a normal model in each agent's decentralized optimization, and that this "sweet spot" corresponds to minimal free energy for the group. At the sweet spot, an agent can predict what the group will do and the group is not surprised by the agent. However, there is an asymmetry. A higher capacity model for an agent makes it harder for the individual to learn, as there are more parameters. Simultaneously, a higher capacity model for the group, implemented as a higher capacity model for each member agent, makes it easier for a group to integrate a new member. To optimize for a group of agents then requires one to make a trade-off in capacity, as each individual agent seeks to decrease capacity, but there is pressure from the group to increase capacity of all members. This pressure exists because as individual agent's capacities are reduced, so too are their abilities to model other agents, and thereby to establish pro-social behavioural patterns. I then consider a basic two-level (dual process) Bayesian model of social reasoning and a set of three parameters of capacity that are required to implement such a model. Considering these three capacities as dependent elements in a free energy minimization for a group leads to a "sweet surface" in a three-dimensional space defining the triplet of parameters that each agent must use should they hope to minimize free energy as a group. Finally, I relate these three parameters to three notions of freedom and equality in human social organization, and postulate a correspondence between freedom and model capacity. That is, models with higher capacity, have more freedom as they can interact with more datasets. [ABSTRACT FROM AUTHOR]