Pixelating Familiar People in the Media: Should Masking Be Taken at Face Value?

This study questions the effectiveness of masking faces by means of pixelation on television or in newspapers. Previous studies have shown that masking just the face leads to unacceptably high recognition levels, making it likely that participants also use other cues for recognition, such as hairstyle or clothes. In the current study we investigate this possibility by means of an identification task in which participants had to identify (partially) masked images of familiar people. To demonstrate that non-facial cues become increasingly important for recognition as faces are masked more strongly, we manipulated the size of the masked area and the degree of pixelation. Confirming our expectations, increasing the size of masked area or its level of deterioration led to lower recognition rates. More importantly, also an interaction effect between the two variables emerged, showing that additional visual information partly compensates the downswing in recognition when masking becomes stronger. Although in some conditions low recognition rates were found, masking was never a hundred percent effective, making it clear that the media should approach this issue with care. Implications of our findings and future directions are considere

Yet another look at thirty categorization results

We re-analyzed thirty data sets reported in the literature and summarized by Smith and Minda (2000), based on Medin and Schaffer’s (1978) 5-4 structure. In their meta-analysis, Smith and Minda (2000) focused on comparing the prototype and the exemplar model. In our meta-analysis, we applied the varying abstraction model, a multiple-prototype model proposed by Vanpaemel, Storms, and Ons (2005), that reduces to the prototype and the exemplar model in special cases. While we found a lot of heterogeneity in the best performing model across data sets, overall, the exemplar model turned out to account for the data best. However, a slight modification of the exemplar model improved performance in one condition, while in another condition, a modification of the prototype model recovered the data best.11status: publishe

Finding our way in the social world exploring the dimensions underlying social classification

People readily use social categories in their daily interactions with others. Although many scholars have focused on social categorization, they have largely neglected the cognitive representation of stimuli as a basis of this process. The present work aims to determine what dimensions are commonly used to organize the social world. The main dimensions of the social mental map are extracted from sorting data pertaining to a wide variety of social stimuli. Dimensions reflecting conventionalism, age, gender, physical versus cognitive orientation, warmth, and deviance are revealed. Furthermore, we show important individual differences in the extent to which each of these dimensions are attended to. We also establish the stability and reliability of our findings in a follow-up and a replication study

Stripping the Political Cynic: A Psychological Exploration of the Concept of Political Cynicism

The high level of political cynicism in contemporary society is often considered a serious threat to democracy. The concept, however, has received only scant attention in psychology. The current work introduces political cynicism and extensively explores its psychological implications by investigating the concept’s validity, predictive utility, and status as a dispositional variable. First, political cynicism is empirically distinguishable from the closely related constructs social cynicism and political trust. Furthermore, political cynicism is strongly related to a wide range of political variables, such as voting intentions, political normlessness, and political estrangement, as well as to broad social attitudes and racial prejudice. Finally, we show that political cynicism yields limited, but meaningful relationships with Neuroticism and Agreeableness, although social cynicism is more clearly related to the Five-Factor Model personality dimensions. It is therefore concluded that political cynicism can be reliably measured and distinguished from closely related concepts, and that it yields meaningful relationships with other relevant psychological variables

SCA with rotation to distinguish common and distinctive information in linked data

Often data are collected that consist of different blocks that all contain information about the same entities (e. g., items, persons, or situations). In order to unveil both information that is common to all data blocks and information that is distinctive for one or a few of them, an integrated analysis of the whole of all data blocks may be most useful. Interesting classes of methods for such an approach are simultaneous-component and multigroup factor analysis methods. These methods yield dimensions underlying the data at hand. Unfortunately, however, in the results from such analyses, common and distinctive types of information are mixed up. This article proposes a novel method to disentangle the two kinds of information, by making use of the rotational freedom of component and factor models. We illustrate this method with data from a cross-cultural study of emotions

Social classification occurs at the subgroup level evidence based on a multidimensional scaling study

Although the categorization of novel social stimuli according to general qualities of gender, age, and race is known to be automatic and primordial, categorizing stimuli into more specific social subgroups (e.g., hippies or businesswomen) is much more informative and cognitively efficient. In this paper, we show that social stimuli are more likely to be grouped into subgroups with an intermediate degree of specificity than into broad, general categories or narrow, highly specific categories. Furthermore, we show that category membership at the intermediate subgroup level predicts social judgments more efficiently than category membership at a more general or more specific level. We discuss the consequences of our results for social cognition and cognitive categorization

Beyond exemplars and prototypes as memory representations of natural concepts: A clustering approach

Categorization in well-known natural concepts is studied using a special version of the Varying Abstraction Framework (Vanpaemel, W., & Storms, G. (2006). A varying abstraction framework for categorization. Manuscript submitted for publication; Vanpaemel, W., Storms, G., & Ons, B. (2005). A varying abstraction model for categorization. In B. Bara, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the 27th annual conference of the Cognitive Science Society (pp. 2277-2282). Mahwah, NJ: Lawrence Erlbaum). This framework assumes a continuum between highly abstract memory representations (prototypes) and highly detailed representations of concept members (exemplars). Comparison stimuli for categorization are obtained by taking for each category the centroids of a set of clusters, produced by K-means clustering, effectively producing the Generalized Context Model (GCM; Nosofsky, R. M. (1986) Attention, similarity, and the identification-categorization relationship. Journal of Experimental Psychology: General. 115, 39-57) and the Single-Prototype Model as extreme cases. The clustering version of the Varying Abstraction Framework was fit on a set of novel, to-be-classified fruits and vegetables (Smits, Storms, Rosseel, & De Boeck, 2002) and on a new set of novel, to-be-classified carnivores and herbivores. Better fit values were clearly obtained for a model based on intermediately abstract representations, indicating a strategy where people compare the novel stimuli to a set of multiple prototypes. This sheds a new light on the prototype versus exemplar discussion that has dominated the literature over the past 25 years. © 2006 Elsevier Inc. All rights reserved.status: publishe