(How) does positive and negative extended cross‐group contact predict direct cross‐group contact and intergroup attitudes?
Bibliographic record
Abstract
Abstract Knowing that fellow ingroup members have cross‐group contact can affect how people think, feel, and behave towards an out‐group. Previous research on extended contact focused almost exclusively on positive cross‐group interactions, neglecting the fact that extended contact can also be negative. In this contribution, we introduce negative extended contact and investigate how both forms of extended contact predict direct cross‐group contact and intergroup attitudes. In two cross‐sectional studies (N 1 = 286, N 2 = 237), we found evidence that positive and negative extended contact uniquely predict intergroup attitudes, and that direct cross‐group contact mediates this effect. In , we also provide initial evidence that extended contact might either prepare for or impair direct contact by changing ingroup norms and intergroup self‐efficacy, which in turn influence feelings of intergroup anxiety.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".