I'm Not Prejudiced,But…: A Deeper Look at Racial Attitudes*

Black and white people experience race relations from different social positions, thus, interpret questions about race relations differently. Structured interviews were conducted with a random sample of residents from Philadelphia and Meridian, Mississippi. These data indicate that there is a wider gap between these blacks and whites regarding their perceptions of discrimination than the gap documented by national surveys. There are interesting differences in the way the two groups interpret themselves as racist, or not, and how they remember their communities’interracial history. Content analysis is used to demonstrate differences in the understanding of race relations, segregation, and perceived danger from racially motivated violence.     

Computing Normal Form Perfect Equilibria for Extensive Two‐Person Games

This paper presents an algorithm for computing an equilibrium of an extensive two‐person game with perfect recall. The method is computationally efficient by virtue of using the sequence form, whose size is proportional to the size of the game tree. The equilibrium is traced on a piecewise linear path in the sequence form strategy space from an arbitrary starting vector. If the starting vector represents a pair of completely mixed strategies, then the equilibrium is normal form perfect. Computational experiments compare the sequence form and the reduced normal form, and show that only the sequence form is tractable for larger games.     

Many Faces of Openness in Adoption: Perspectives of Adopted Adolescents and Their Parents

Parents and adolescents (mean age, 15.7 years) from 177 adoptive families participating in the second wave of the Minnesota/Texas Adoption Research Project were interviewed about their post-adoption contact arrangements. The sample included families with no contact, stopped contact, contact without meetings, and contact with face-to-face meetings between the adolescent and birth mother. Openness arrangements were dynamic, and different openness arrangements were associated with different experiences and feelings. Adoptive families with contact reported having higher levels of satisfaction about their openness arrangements, experiencing more positive feelings about the birth mother, and possessing more factual and personal knowledge about the birth mother than did families without contact. Adolescents and adoptive mothers in the contact with meetings group reported the greatest satisfaction with their openness arrangements; those with no contact or stopped contact reported the least satisfaction with their arrangements. Participants having no contact were more likely to want the intensity of contact to increase in the future rather than stay the same. Many participants already having contact wanted it to increase in the future. Fewer than 1 percent of all participants wanted to see the intensity of contact decrease.     

Using latent class analysis to detect behavioral patterns in systems of observational variables

Behavioral observation is widely used for data gathering in evaluation research. Yet it leaves the investigator with unique problems. Usually, multiple observations result in a hierarchical data set, where numerous data records exist for each subject. Researchers face data reduction problems at least at two levels. First, there is the well-known and often-addressed problem of reducing the number of variables in a data set with only one information record per individual. Second, there is the problem of summarizing data at the individual subject level. The easiest way to perform this latter type of aggregation involves using univariate summary measures as probabilities of “using” an item, means, or standard deviations for each item per subject. Other standard procedures include first order interactions between pairs of items. However, use of pair-wise interactions is restricted because of variable dependence within each subject (this Affects e.g. factor analysis), or because of the relatively high number of single observations (this Affects e.g., cluster analysis). In this paper we propose employing Latent Class Analysis (LCA) to reduce the amount of information in observational data sets. In a first step, LCA allows one to specify intraindividual behavior patterns. In a second step, LCA allows one to derive meaningful summary scores for each individual. The two steps are illustrated using data that describe peer play competence in Swedish toddlers.