Can Social Contact Reduce Prejudice and Discrimination? Evidence from a Field Experiment in Nigeria
Bibliographic record
Abstract
Can positive social contact between members of antagonistic groups reduce prejudice and discrimination? Despite extensive research on social contact, observational studies are difficult to interpret because prejudiced people may select out of contact with out-group members. We overcome this problem by conducting an education-based, randomized field experiment—the Urban Youth Vocational Training program (UYVT)—with 849 randomly sampled Christian and Muslim young men in riot-prone Kaduna, Nigeria. After sixteen weeks of positive intergroup social contact, we find no changes in prejudice, but heterogeneous-class subjects discriminate significantly less against out-group members than subjects in homogeneous classes. We trace this finding to increased discrimination by homogeneous-class subjects compared to non-UYVT study participants, and we highlight potentially negative consequences of in-group social contact. By focusing on skill-building instead of peace messaging, our intervention minimizes reporting bias and offers strong experimental evidence that intergroup social contact can alter behavior in constructive ways, even amid violent conflict.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".