On the Generalization of Intergroup Contact: A Taxonomy of Transfer Effects
Bibliographic record
Abstract
The contact hypothesis proposes that bringing groups together under favorable conditions can improve intergroup relations. It is now well established that intergroup contact can improve attitudes not only toward the out-group as a whole but also toward other, noncontacted groups ( secondary transfer effect). We review evidence of a further, higher-order generalization effect whereby intergroup contact also impacts more general cognitive processes outside of the intergroup context (i.e., tertiary transfer effects). We present a taxonomy of transfer effects that explains these generalization effects as distinct outcomes of the contact process yet contingent on the same component process, specifically, the assessment of the semantic distance between the target (e.g., contacted individual) and the frame (e.g., group prototype). This conceptualization provides an explanatory framework for uniting the disparate forms of transfer effect in the contact literature, clarifying why primary and secondary transfer effects are facilitated by low semantic distance and why contact is more cognitively demanding under conditions of high semantic distance, but with greater potential for cognitive growth.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".