Self‐Expansion and Intergroup Contact: Expectancies and Motives to Self‐Expand Lead to Greater Interest in Outgroup Contact and More Positive Intergroup Relations
Bibliographic record
Abstract
Sixty years of research on intergroup contact demonstrates that positive interactions across group boundaries can improve intergroup attitudes and can contribute to forging tolerant, integrated, multicultural societies. However, to fully realize the benefits of growing diversity around the globe, individuals need to exploit opportunities for intergroup contact that are available to them. Yet, it is relatively unknown why people might deliberately engage in cross‐group interactions and how individuals’ expectations and motives prepare them to develop positive interpersonal relationships with outgroup members. In this article, we begin to address these research gaps. We discuss the self‐expansion model and present new evidence that is consistent with this model. Two studies, one correlational in a cross‐cultural setting and the other experimental, show the value of high self‐expansion expectancies and motivation in promoting interest in and producing more and higher quality interactions across group boundaries. We discuss implications of these findings for policy and intervention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".