The impact of informant gender on children’s endorsement of scientific and non-scientific information

By roughly 6 years of age, children acquire the stereotype that men are more competent than women in science, technology, engineering, and mathematics (STEM), potentially leading to greater trust in scientific information provided by men. This study tested whether 3- to 8-year-old children differentially endorsed conflicting information about science and toys presented by male and female informants depicted as a ‘man’ and ‘woman’ (Exp1) or ‘scientists’ (Exp2). Children were expected to endorse toy testimony from gender-matched informants; thus, the key question concerned endorsement of science testimony. In Exp1 (N = 149), boys and girls showed a same-gender informant preference for toy testimony; however, girls endorsed the male informant's testimony more for science than for toys – but only when tested by a male experimenter. In Exp2 (N = 264), boys and girls showed a same-gender preference, irrespective of content. Findings suggest that STEM-related gender stereotypes might lead girls to trust scientific information presented by men over women in certain contexts.     

The Creativity Matrix: Spotlights and Blind Spots in Our Understanding of the Phenomenon

In this paper, we organize past and present theories and models of creativity by using a new conceptual framework—the creativity matrix—with the aim of highlighting the dimensions of creativity we know a lot about and those we tend to either ignore or find difficult to study. This matrix is formed by bringing together a developmental model of creativity (the 4 C's) and a structural one (the 5 A's). We start by briefly describing these two conceptual frameworks, and then, we proceed to exploring the matrix itself by describing how the 5 A's are dynamically organized at each “level” of the 4 C's. Importantly, our overview of the matrix is informed by existing models and concepts that address one of more of the C's and the A's. This gives us a unique opportunity to take stock of what has been studied so far and, toward the end, consider new avenues for the development of theory and research agendas within creativity studies.     

Rivals without a cause? Relative performance feedback creates destructive competition despite aligned incentives

Whether people compete or cooperate with each other has consequences for their own performance and that of organizations. To explain why people compete or cooperate, previous research has focused on two main factors: situational outcome structures and personality types. Here, we propose that—above and beyond these two factors—situational cues, such as the format in which people receive feedback, strongly affect whether they act competitively, cooperatively, or individualistically. Results of a laboratory experiment support our theorizing: After receiving ranking feedback, both students and experienced managers treated group situations with cooperative outcome structures as competitive and were in consequence willing to forgo guaranteed financial gains to pursue a—financially irrelevant—better rank. Conversely, in dilemma situations, feedback based on the joint group outcome led to more cooperation than ranking feedback. Our study contributes to research on competition, cooperation, interdependence theory, forced ranking, and the design of information environments.     

ACQUISITION AND FUNCTIONAL ANALYSIS OF MANDING WITH AUTISTIC STUDENTS

Three autistic students were trained to request a specific object from an adult “supplier” with the sentence, “Give me —” and to deliver that object to another adult, the “director.” Subsequently, the degree to which the object offered by the supplier controlled the “Give me —” verbal response was assessed by delivering to the student an object other than the one requested. Despite knowing the names of all objects used in the experiment, students accepted and delivered to the director any object offered by the supplier regardless of its match with the requested object. After training to say “That's not it. Give me —” when nonrequested objects were offered, students responded differentially to requested and nonrequested objects, suggesting control of the “Give me —” response by the requested object, a characteristic of a mand. These results generalized across settings and objects. Results are discussed in terms of the training technique to establish manding and the functional analysis of the resulting verbal behavior.     

Typical delay determines waiting time on periodic-food schedules: Static and dynamic tests

Pigeons and other animals soon learn to wait (pause) after food delivery on periodic-food schedules before resuming the food-rewarded response. Under most conditions the steady-state duration of the average waiting time, t, is a linear function of the typical interfood interval. We describe three experiments designed to explore the limits of this process. In all experiments, t was associated with one key color and the subsequent food delay, T, with another. In the first experiment, we compared the relation between t (waiting time) and T (food delay) under two conditions: when T was held constant, and when T was an inverse function of t. The pigeons could maximize the rate of food delivery under the first condition by setting t to a consistently short value; optimal behavior under the second condition required a linear relation with unit slope between t and T. Despite this difference in optimal policy, the pigeons in both cases showed the same linear relation, with slope less than one, between t and T. This result was confirmed in a second parametric experiment that added a third condition, in which T + t was held constant. Linear waiting appears to be an obligatory rule for pigeons. In a third experiment we arranged for a multiplicative relation between t and T (positive feedback), and produced either very short or very long waiting times as predicted by a quasi-dynamic model in which waiting time is strongly determined by the just-preceding food delay.     

A general model for the analysis of multilevel data

A general model is developed for the analysis of multivariate multilevel data structures. Special cases of the model include repeated measures designs, multiple matrix samples, multilevel latent variable models, multiple time series, and variance and covariance component models.We would like to acknowledge the helpful comments of Ruth Silver. We also wish to thank the referees for helping to clarify the paper. This work was partly carried out with research funds provided by the Economic and Social Research Council (U.K.).     

Test theory without an answer key

A general model is presented for homogeneous, dichotomous items when the answer key is not known a priori. The model is structurally related to the two-class latent structure model with the roles of respondents and items interchanged. For very small sets of respondents, iterative maximum likelihood estimates of the parameters can be obtained by existing methods. For other situations, new estimation methods are developed and assessed with Monte Carlo data. The answer key can be accurately reconstructed with relatively small sets of respondents. The model is useful when a researcher wants to study objectively the knowledge possessed by members of a culturally coherent group that the researcher is not a member of.This research was supported by NSF Grant No. SES-8320173 to the authors. We gratefully acknowledge comments and suggestions from John Boyd, Tarow Indow, and Kathy Maher as well as the editor and several anonymous referees.     

Hierarchical classes: Model and data analysis

A discrete, categorical model and a corresponding data-analysis method are presented for two-way two-mode (objects × attributes) data arrays with 0, 1 entries. The model contains the following two basic components: a set-theoretical formulation of the relations among objects and attributes; a Boolean decomposition of the matrix. The set-theoretical formulation defines a subset of the possible decompositions as consistent with it. A general method for graphically representing the set-theoretical decomposition is described. The data-analysis algorithm, dubbed HICLAS, aims at recovering the underlying structure in a data matrix by minimizing the discrepancies between the data and the recovered structure. HICLAS is evaluated with a simulation study and two empirical applications.This research was supported in part by a grant from the Belgian NSF (NFWO) to Paul De Boeck and in part by NSF Grant BNS-83-01027 to Seymour Rosenberg. We thank Iven Van Mechelen for clarifying several aspects of the Boolean algebraic formulation of the model and Phipps Arabie for his comments on an earlier draft.     

A content analysis of the conversational behavior of accepted and rejected children

The present study was designed to assess whether the conversational behavior of children separated into accepted, rejected, and mixed-status dyads differed along the dimensions of listening to, paying attention to, and indicating interest in their dyadic partner. Conversations of 40 third-grade dyads were analyzed as they occurred in a 2- min waiting period and a 4- min conversation period. Seventeen categories of verbal behaviors that indexed these dimensions were used as content codes. Multivariate analyses of variance performed on the observational data yielded significant main effects for status, sex, and experimental condition. Results are interpreted in terms of previous social skills research, and suggestions for future research are offered.