Motor ability and self-esteem: The mediating role of physical self-concept and perceived social acceptance

Objectives: One important issue in sport and exercise psychology is to determine to what extent sports and exercise can help to increase self-esteem, and what the underlying mechanism might be. Based on the exercise and self-esteem model (EXSEM) and on findings from the sociometer theory, the mediating effect of physical self-concept and perceived social acceptance on the longitudinal relationship between motor ability and self-esteem was investigated. Design: Longitudinal study with three waves of data collection at intervals of ten weeks each. Method: 428 adolescents (46.3 % girls, mean age = 11.9, SD = .55) participated in the study, in which they performed three motor ability tests and completed paper-and-pencil questionnaires for physical self-concept and perceived social acceptance, as well as for self-esteem, at all three measuring points. Results: Using structural equation modelling procedures, the multiple mediation model revealed both physical self-concept and perceived social acceptance to be mediators between motor ability and self-esteem in the case of boys. In girls, on the other hand, the mediation between motor ability and self-esteem only takes place via physical self-concept. Conclusions: Gender differences in the relationship between motor ability and self-esteem suggest gender-specific interventions aimed at promoting self-concept.

Social Salience and the Sociolinguistic Monitor: a Case Study of ING and TH-fronting in Britain

This article examines the role of social salience, or the relative ability of a linguistic variable to evoke social meaning, in structuring listeners’ perceptions of quantitative sociolinguistic distributions. Building on the foundational work of Labov et al. (2006, 2011) on the “sociolinguistic monitor” (a proposed cognitive mechanism responsible for sociolinguistic perception), we examine whether listeners’ evaluative judgments of speech change as a function of the type of variable presented. We consider two variables in British English, ING and TH-fronting, which we argue differ in their relative social salience. Replicating the design of Labov et al.’s studies, we test 149 British listeners’ reactions to different quantitative distributions of these variables. Our experiments elicit a very different pattern of perceptual responses than those reported previously. In particular, our results suggest that a variable’s social salience determines both whether and how it is perceptually evaluated. We argue that this finding is crucial for understanding how sociolinguistic information is cognitively processed.

Recommendations for sex/gender neuroimaging research: Key principles and implications for research design, analysis and interpretation

Neuroimaging (NI) technologies are having increasing impact in the study of complex cognitive and social processes. In this emerging field of social cognitive neuroscience, a central goal should be to increase the understanding of the interaction between the neurobiology of the individual and the environment in which humans develop and function. The study of sex/gender is often a focus for NI research, and may be motivated by a desire to better understand general developmental principles, mental health problems that show female-male disparities, and gendered differences in society. In order to ensure the maximum possible contribution of NI research to these goals, we draw attention to four key principles—overlap, mosaicism, contingency and entanglement—that have emerged from sex/gender research and that should inform NI research design, analysis and interpretation. We discuss the implications of these principles in the form of constructive guidelines and suggestions for researchers, editors, reviewers and science communicators.

Ethical Consumption and Social Context: Experimental Evidence from Germany and the United States

This research examines the role of social context in ethical consumption, specifically, the extent to which anonymity and social control influence individuals' decisions to purchase organic and Fair Trade coffee. Our research design overcomes biases of prior research by combining framing and discrete choice experiments in a survey. We systematically vary coffee growing method (organic or not), import status (Fair Trade or not), flavor, and price across four social contexts that vary in degree of anonymity and normative social control. The social contexts are buying coffee online, in a large grocery store, in a small neighborhood shop, and for a meeting of a human rights group. Subjects comprise 1,103 German and American undergraduate students. We find that social context indeed influences subjects' ethical consumer decisions, especially in situations with low anonymity and high social control. In addition, gender, coffee buying, and subjective social norms trigger heterogeneity regarding stated ethical consumption and the effects of social context. These results suggest previous research has underestimated the relevance of social context for ethical consumption and overestimated altruistic motives of ethical consumers. Our study demonstrates the great potential of discrete choice experiments for the study of social action and decision making processes in sociology.

Explicit vs implicit affiliation motives predict different social behavior in sports competition

Objectives The present study investigated the predictive value of the explicit and implicit affiliation motive for social behavior in sport competitions. From an information processing perspective, an explicit motive is linked to verbal cues and respondent behavior. The implicit motive in turn is linked to nonverbal stimuli and operant behavior (McClelland, Koestner, & Weinberger, 1989; Schultheiss, 2008). Both respondent affiliative behavior (e.g., verbal interactions with teammates) and operant nonverbal social behavior (e.g., pleasant to opponents) can be observed in racquet sports team competitions. Design & Methods Fifty-two male racquet sportsmen completed the Personality Research Form (explicit affiliation motive) and the Operant Motive Test (implicit affiliation motive). Motive measures were used to predict social behavior during competitions using multiple regression analyses. To this aim real competitive matches were videotaped and analyzed. Results Results show that the explicit affiliation motive is associated with time spent in verbal team contact. The implicit affiliation motive, by contrast, is linked to pleasant nonverbal behavior shown toward opponents. Conclusions Findings suggest that implicit and explicit affiliation motives predict different kinds of social behavior in sports competition respectively. Indirect motive measures may be of additional predictive value for different behavior in real sports settings.

Multinomial goodness-of-fit: large sample tests with survey design correction and exact tests for small samples

I introduce the new mgof command to compute distributional tests for discrete (categorical, multinomial) variables. The command supports largesample tests for complex survey designs and exact tests for small samples as well as classic large-sample x2-approximation tests based on Pearson’s X2, the likelihood ratio, or any other statistic from the power-divergence family (Cressie and Read, 1984, Journal of the Royal Statistical Society, Series B (Methodological) 46: 440–464). The complex survey correction is based on the approach by Rao and Scott (1981, Journal of the American Statistical Association 76: 221–230) and parallels the survey design correction used for independence tests in svy: tabulate. mgof computes the exact tests by using Monte Carlo methods or exhaustive enumeration. mgof also provides an exact one-sample Kolmogorov–Smirnov test for discrete data.

The ring vaccination trial: a novel cluster randomised controlled trial design to evaluate vaccine efficacy and effectiveness during outbreaks, with special reference to Ebola

A World Health Organization expert meeting on Ebola vaccines proposed urgent safety and efficacy studies in response to the outbreak in West Africa. One approach to communicable disease control is ring vaccination of individuals at high risk of infection due to their social or geographical connection to a known case. This paper describes the protocol for a novel cluster randomised controlled trial design which uses ring vaccination.In the Ebola ça suffit ring vaccination trial, rings are randomised 1:1 to (a) immediate vaccination of eligible adults with single dose vaccination or (b) vaccination delayed by 21 days. Vaccine efficacy against disease is assessed in participants over equivalent periods from the day of randomisation. Secondary objectives include vaccine effectiveness at the level of the ring, and incidence of serious adverse events.Ring vaccination trials are adaptive, can be run until disease elimination, allow interim analysis, and can go dormant during inter-epidemic periods.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.

The American Myth of Markets in Social Policy: Ideological Roots of Inequality

The American Myth of Markets in Social Policy examines how implementing American tropes in policy design inadvertently frustrates policy goals. It investigates multiple market-oriented designs including funding for private organizations to deliver public services, funding for individuals to buy services, and policies incentivizing or mandating private actors to provide social policy. The author shows that these solutions often not only fail to achieve social goals, but, in fact, actively undermine them, for example saddling the poor with debt or encouraging discrimination. The book carefully details the mechanisms through which this occurs, for example a mismatch between program goals and either contract terms or individual preferences. The author examines several policies in depth, covering universal social insurance programs like healthcare and pensions, as well as smaller interventions like programs for the homeless. The author builds the argument using detailed empirical evidence as well as anecdote, keeping the book accessible and entertaining.

Multinomial goodness-of-fit: large sample tests with survey design correction and exact tests for small samples

A new Stata command called -mgof- is introduced. The command is used to compute distributional tests for discrete (categorical, multinomial) variables. Apart from classic large sample $\chi^2$-approximation tests based on Pearson's $X^2$, the likelihood ratio, or any other statistic from the power-divergence family (Cressie and Read 1984), large sample tests for complex survey designs and exact tests for small samples are supported. The complex survey correction is based on the approach by Rao and Scott (1981) and parallels the survey design correction used for independence tests in -svy:tabulate-. The exact tests are computed using Monte Carlo methods or exhaustive enumeration. An exact Kolmogorov-Smirnov test for discrete data is also provided.

Social Network Analysis and Qualitative Comparative Analysis: Their mutual benefit for the explanation of policy network structures

By switching the level of analysis and aggregating data from the micro-level of individual cases to the macro-level, quantitative data can be analysed within a more case-based approach. This paper presents such an approach in two steps: In a first step, it discusses the combination of Social Network Analysis (SNA) and Qualitative Comparative Analysis (QCA) in a sequential mixed-methods research design. In such a design, quantitative social network data on individual cases and their relations at the micro-level are used to describe the structure of the network that these cases constitute at the macro-level. Different network structures can then be compared by QCA. This strategy allows adding an element of potential causal explanation to SNA, while SNA-indicators allow for a systematic description of the cases to be compared by QCA. Because mixing methods can be a promising, but also a risky endeavour, the methodological part also discusses the possibility that underlying assumptions of both methods could clash. In a second step, the research design presented beforehand is applied to an empirical study of policy network structures in Swiss politics. Through a comparison of 11 policy networks, causal paths that lead to a conflictual or consensual policy network structure are identified and discussed. The analysis reveals that different theoretical factors matter and that multiple conjunctural causation is at work. Based on both the methodological discussion and the empirical application, it appears that a combination of SNA and QCA can represent a helpful methodological design for social science research and a possibility of using quantitative data with a more case-based approach.