Three Experimental Approaches to Measure the Social Context Dependence of Prejudice Communication and Discriminatory Behavior

Empirical research on discrimination is faced with crucial problems stemming from the specific character of its object of study. In democratic societies the communication of prejudices and other forms of discriminatory behavior is considered socially undesirable and depends on situational factors such as whether a situation is considered private or whether a discriminatory consensus can be assumed. Regular surveys thus can only offer a blurred picture of the phenomenon. But also survey experiments intended to decrease the social desirability bias (SDB) so far failed in systematically implementing situational variables. This paper introduces three experimental approaches to improve the study of discrimination and other topics of social (un-)desirability. First, we argue in favor of cognitive context framing in surveys in order to operationalize the salience of situational norms. Second, factorial surveys offer a way to take situational contexts and substitute behavior into account. And third, choice experiments – a rather new method in sociology – offer a more valid method of measuring behavioral characteristics compared to simple items in surveys. All three approaches – which may be combined – are easy to implement in large-scale surveys. Results of empirical studies demonstrate the fruitfulness of each of these approaches.

A Logarithmic Image Prior for Blind Deconvolution

Blind Deconvolution consists in the estimation of a sharp image and a blur kernel from an observed blurry image. Because the blur model admits several solutions it is necessary to devise an image prior that favors the true blur kernel and sharp image. Many successful image priors enforce the sparsity of the sharp image gradients. Ideally the L0 “norm” is the best choice for promoting sparsity, but because it is computationally intractable, some methods have used a logarithmic approximation. In this work we also study a logarithmic image prior. We show empirically how well the prior suits the blind deconvolution problem. Our analysis confirms experimentally the hypothesis that a prior should not necessarily model natural image statistics to correctly estimate the blur kernel. Furthermore, we show that a simple Maximum a Posteriori formulation is enough to achieve state of the art results. To minimize such formulation we devise two iterative minimization algorithms that cope with the non-convexity of the logarithmic prior: one obtained via the primal-dual approach and one via majorization-minimization.

Family Models of In(ter)dependence: Cultural Change and the Question of Universal Needs

I will start by discussing some aspects of Kagitcibasi’s Theory of Family Change: its current empirical status and, more importantly, its focus on universal human needs and the consequences of this focus. Family Change Theory’s focus on the universality of the basic human needs of autonomy and relatedness and its culture-level emphasis on cultural norms and family values as reflecting a culture’s capacity for fulfilling its members’ respective needs shows that the theory advocates balanced cultural norms of independence and interdependence. As a normative theory it therefore postulates the necessity of a synthetic family model of emotional interdependence as an alternative to extreme models of total independence and total interdependence. Generalizing from this I will sketch a theoretical model where a dynamic and dialectical process of the fit between individual and culture and between culture and universal human needs and related social practices is central. I will discuss this model using a recent cross-cultural project on implicit theories of self/world and primary/secondary control orientations as an example. Implications for migrating families and acculturating individuals are also discussed.