Replicating and extending Sengupta et al. (2023): Contact predicts no within-person longitudinal outgroup-bias change.
Bibliographic record
Abstract
Intergroup contact has long been touted as a premier means to reduce prejudice and forge positive bonds with outgroups.Given its origins in psychological research, it is perhaps of little surprise that contact is expected to induce change within people over time.Yet using random-intercepts crossed-lagged modelling that parses within-person from between-person effects, Sengupta and colleagues (in press) recently found no evidence of within-person change, only unexplained between-person effects, regarding contact's effects on outgroup solidarity in New Zealand.We conceptually replicated their study, focusing on modern racism and an affect thermometer as the outcomes, in a 3-wave study of White Brits (NT1 = 946, NT2 = 667, NT3 = 591) and their attitudes toward foreigners.We replicated the general pattern by Sengupta and colleagues, confirming between-person effects without withinperson effects, suggestive of third-variable explanations.As a novel finding, we discover that differences in social dominance orientation (SDO) and right-wing authoritarianism (RWA) can account for the observed between-person effects.Problematically for contact theory, contact effects, at least those relying on self-reported accounts, increasingly appear to reflect differences between people (person-factors) rather than being context-driven (situationfactors) -such that those lower (vs.higher) in SDO and RWA are more favorable toward outgroups, rather than intergroup contact bringing about positive outcomes itself.Implications for theory development and intervention are discussed.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".