Lazy, Dumb, or Industrious: When Stereotypes Convey Attribution Information in the Classroom

Teachers' Typology of Student Categories: A Cluster Analytic Study

The present study demonstrates the application of cluster analysis to examine the typology of student categories of novice Luxembourgish teachers. Student categories are mental representations of groups of students in which teachers classify their students. The investigation of student categories is a relevant topic in education, because subsequent assessments of students may be biased by prior...

African American Boys' and Girls' Causal Attributions about Math, English, and Science are Shaped by Gender Stereotypes, Influence Classroom Engagement, and Change across the High School Years

When stereotypes get in the way: stereotypes obstruct stereotype-inconsistent trait inferences.

There is a growing body of evidence indicating that people spontaneously make trait inferences while observing the behavior of others. The present article reports a series of 5 experiments that examined the influence of stereotypes on the spontaneous inference of traits. Results consistently showed weaker spontaneous trait inferences for stereotype-inconsistent behavioral information than for s...

Overprivileged, self-absorbed, dumb jocks: exploration of stereotypes of student-athletes

In this study, lists of traits typically associated with several groups of students were created using empirically supported methods. Specifically, these traits were grouped into a taxonomy based on the extent to which they were classified as being stereotypical for male student-athletes, female student-athletes, male non-athlete students, female non-athlete students, masculine individuals, fem...

Using Trust Networks to Improve Data Quality and Recommendations

The boom in social computing has left us with large amounts of information, some of it from automated sensors and some from humans, most of it incomplete, inconsistent, wrong and/or stale. Doctorow noticed that people are lazy, dumb, and at times deceitful, but we still want to use their data rather than none. We will introduce the related notions of Reputation, Trust, Confidence and Reliabilit...