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There exists a racial income gap in America: Blacks earn ∼38% less than Whites, but little is known about its relation to interracial psychological outcomes. Toward this end, the present research examined associations between the Black–White income gap and perceptions of interracial competition and, subsequently, negative intergroup outcomes. Study 1 extracted data from a large, preexisting data set ( N = 2,543) and provided initial support for the hypothesis that higher levels of racial income inequality are associated with increased perceptions of competition. Study 2 then recruited approximately equal numbers of White and Black participants ( N = 1,731) and demonstrated that increases in racial income inequality predict increased perceptions of competition, discrimination, behavioral avoidance, and intergroup anxiety. Implications for theory development and public policy are discussed.

Although past research has suggested that pluralistic ignorance—a mismatch between perceptions of others’ opinions and actual personal opinions—does not occur in every circumstance, no studies have directly investigated variations among different attitude objects. Drawing upon theoretical and analytical approaches based on social representations, this study examines differences between personal opinions and perceived opinions of different groups toward same-sex female parenting (a newly debated attitude object) and working mothers (an older debated attitude object). Using data from a study (N = 743) conducted in Switzerland, the findings indicate that pluralistic ignorance occurs in opinions toward same-sex female parenting. Furthermore, the findings show that pluralistic ignorance arises from false consensus among conservatives and from false uniqueness among liberals.

We created a life-goal assessment drawing from self-determination theory and achievement goal literature, examining its predictive power regarding immoral behavior and subjective well-being. Our source items assessed direction and energization of motivation, via the distinction between intrinsic and extrinsic aims and between intrinsic and extrinsic reasons for acting, respectively. Fused source items assessed four goal complexes representing a combination of direction and energization. Across three studies ( Ns = 109, 121, and 398), the extrinsic aim/extrinsic reason complex was consistently associated with immoral and/or unethical behavior beyond four source and three other goal complex variables. This was consistent with the triangle model of responsibility’s claim that immoral behaviors may result when individuals disengage the self from moral prescriptions. The extrinsic/extrinsic complex also predicted lower subjective well-being, albeit less consistently. Our goal complex approach sheds light on how self-determination theory’s goal contents and organismic integration mini-theories interact, particularly with respect to unethical behavior.

This paper aims to introduce multilevel logistic regression analysis in a simple and practical way. First, we introduce the basic principles of logistic regression analysis (conditional probability, logit transformation, odds ratio). Second, we discuss the two fundamental implications of running this kind of analysis with a nested data structure: In multilevel logistic regression, the odds that the outcome variable equals one (rather than zero) may vary from one cluster to another (i.e. the intercept may vary) and the effect of a lower-level variable may also vary from one cluster to another (i.e. the slope may vary). Third and finally, we provide a simplified three-step “turnkey” procedure for multilevel logistic regression modeling: -Preliminary phase: Cluster- or grand-mean centering variables -Step #1: Running an empty model and calculating the intraclass correlation coefficient (ICC) -Step #2: Running a constrained and an augmented intermediate model and performing a likelihood ratio test to determine whether considering the cluster-based variation of the effect of the lower-level variable improves the model fit -Step #3 Running a final model and interpreting the odds ratio and confidence intervals to determine whether data support your hypothesis Command syntax for Stata, R, Mplus, and SPSS are included. These steps will be applied to a study on Justin Bieber, because everybody likes Justin Bieber.1

We adopted an achievement goal complex framework (studying achievement goals and reasons connected to goals) to determine when and why performance goals predict exploitation of others’ knowledge. We hypothesized that: (i) when selective assessment is used (exams aiming to select a limited number of individuals), the link between performance goals and exploitation orientation is stronger; (ii) the reason why is that selective assessment fosters performance goals regulated by controlled reasons. Study 1 (N = 166) supported these hypotheses in a “real world” environment, comparing students enrolled in programs using non-selective versus selective assessment (but having a majority of common courses). Then, an experimental causal-chain-like design was used. In Study 2 (N = 187), presenting an intelligence test as selective (vs. [self-]evaluative) predicted controlled reasons connected to performance goals. In Study 3 (N = 192), inducing performance goals using controlling (vs. autonomy-supportive) language predicted exploitation orientation, indirectly impairing information-sharing behaviors. The results contribute to the understanding of both the structural antecedents and interpersonal consequences of achievement goal complexes.

Confirmation is a widespread tendency to seek, use, interpret or remember information in such a way as to corroborate one’s hypothesis. We review various conceptions of confirmation and classify th...

International audience; In primary school, learning fractions is a central mathematical objective. However, the mastery of basic procedures involving fractions presents a difficulty for many students. The aim of the current intervention is to introduce structured cooperative learning as means to improve students' learning, particularly for average achievers. Previous research has underscored that heterogeneous groups might be deleterious for average achievers because they are excluded by the teacher learner relationships that is likely to take place between low and high achievers students. This intervention proposes structuring interactions in order to boost the learning of average achievers in heterogeneous groups. We hypothesize that highly structured cooperative learning should improve average achievers' understanding of the content-targeted in group work as well as progress in terms of fractions learning, when compared to low-structured cooperative learning. In this intervention, 108 fifth graders worked cooperatively in heterogeneous triads (a low, average, and high achiever). The triads had to express the length of one segment using three rulers with different sub-units and respecting three mathematical skills regarding fractions. Triads were randomly assigned to a low-structured or high-structured cooperative learning condition. In the low-structured condition, no specific structure was provided. (i.e., they organized their cooperative work as they wished). In the high-structured condition, each student became an expert for one part before working in the triad and endorsed different responsibilities. The results indicated that highly structured cooperative learning favors the understanding of the targeted task, especially for average-ability students. Moreover, students at all levels progressed from the baseline test to the post-test. Indeed, low and high achievers had the same progression in both conditions, whereas average achievers progressed more in the highly structured condition. Results are discussed in terms of new teaching methods that could efficiently increase average achievers’ performances.