Are social value orientations expressed automatically? Decision making in the dictator game

Drawing on the social intuitionist model, the authors studied the hypothesis that social value orientations are expressed automatically in behavior. They compared spontaneous and more deliberated decisions in the dictator game and confirmed that social values determine behavior when responses are based on the automatic system. By means of both mediation and experimental analyses, the authors further demonstrate that the automatic expression of social value orientations is mediated by perceptions of interpersonal closeness. A reasoning process can subsequently override these automatic responses and disconnect decisions from perceptions of interpersonal closeness. This results in lower levels of other-regarding behavior, at least for prosocials.     

Self-Perceived Effects of Pornography Consumption in a Sample of Indonesian University Students

Self-perceived effects of pornography consumption were studied in a sample of university students in Indonesia—a conservative, Muslim majority country with strict anti-pornography laws. Using a cross-sectional design and a modified version of the Pornography Consumption Effect Scale (PCES), we assessed participants' reports of how pornography affected their sexual knowledge, attitude toward sex, sex life, perception of and attitude toward the opposite gender, and life in general. The area of attitude toward sex excepted, the study found that both men and women reported significantly larger positive than negative effects. Further, as compared to women, men reported significantly larger negative effects of their pornography consumption. For both genders, pornography-related variables were found to add significantly to the prediction of both positive and negative self-perceived effects of pornography consumption over and above a number of included control variables.     

Special issue on indigenising educational psychology

The Journal of Psychology in Africa (JPA) is a peer-reviewed journal co-published NISC (Pty) Ltd and Informa UK Limited (trading as Taylor & Francis Group) on behalf of Africa Scholarship Development Enterprize. It is accredited by the Department of Higher Education and Training in South Africa and indexed in the ISI Web of Science. The JPA provides an inter-disciplinary forum for the dissemination of psychological research in Africa and related regions in the context of development. Its core mission is to advance psychological research for the social-cultural and health development in Africanist settings, inclusive of the African diaspora communities around the globe. Research that addresses African heritage realities and opportunities is particularly encouraged. Contributions should attempt a synthesis of local and universal methodologies and applications, contributing to the wider body of knowledge in the applied psychological sciences.     

Detecting intra- and inter-categorical structure in semantic concepts using HICLAS

In this paper, we investigate the hypothesis that people use feature correlations to detect inter- and intra-categorical structure. More specifically, we study whether it is plausible that people strategically look for a particular type of feature co-occurrence that can be represented in terms of rectangular patterns of 1s and 0s in a binary feature by exemplar matrix. Analyzing data from the Animal and Artifact domains, we show that the HICLAS model, which looks for such rectangular structure and which therefore models a cognitive capacity of detecting feature co-occurence in large data bases of features characterizing exemplars, succeeds rather well in predicting inter- and intra-categorical structure.     

Features of graded category structure: Generalizing the family resemblance and polymorphous concept models

Many real-world categories contain graded structure: certain category members are rated as more typical or representative of the category than others. Research has shown that this graded structure can be well predicted by the degree of commonality across the feature sets of category members. We demonstrate that two prominent feature-based models of graded structure, the family resemblance (Rosch & Mervis, 1975) and polymorphous concept models (Hampton, 1979), can be generalized via the contrast model (Tversky, 1977) to include both common and distinctive feature information, and apply the models to the prediction of typicality in 11 semantic categories. The results indicate that both types of feature information play a role in the prediction of typicality, with common features weighted more heavily for within-category predictions, and distinctive features weighted more heavily for contrast-category predictions. The same pattern of results was found in additional analyses employing rated goodness and exemplar generation frequency. It is suggested that these findings provide insight into the processes underlying category formation and representation.     

Idealness and similarity in goal-derived categories: A computational examination

The finding that the typicality gradient in goal-derived categories is mainly driven by ideals rather than by exemplar similarity has stood uncontested for nearly three decades. Due to the rather rigid earlier implementations of similarity, a key question has remained—that is, whether a more flexible approach to similarity would alter the conclusions. In the present study, we evaluated whether a similarity-based approach that allows for dimensional weighting could account for findings in goal-derived categories. To this end, we compared a computational model of exemplar similarity (the generalized context model; Nosofsky, Journal of Experimental Psychology. General 115:39–57, 1986) and a computational model of ideal representation (the ideal-dimension model; Voorspoels, Vanpaemel, & Storms, Psychonomic Bulletin & Review 18:1006-114, 2011) in their accounts of exemplar typicality in ten goal-derived categories. In terms of both goodness-of-fit and generalizability, we found strong evidence for an ideal approach in nearly all categories. We conclude that focusing on a limited set of features is necessary but not sufficient to account for the observed typicality gradient. A second aspect of ideal representations—that is, that extreme rather than common, central-tendency values drive typicality—seems to be crucial.