Symptoms of Paranoia Experienced by Students of Pakistani Heritage in England
Bibliographic record
Abstract
ABSTRACT: Individuals belonging to ethnic minority groups are less likely to experience symptoms of psychosis, such as paranoia, if they live in areas with high proportions of people from the same ethnic background. This effect may be due to processes associated with group belonging (social identification). We examined whether the relationship between perceived discrimination and paranoia was moderated by explicit and implicit Pakistani/English identification among students of Pakistani heritage (N = 119). Participants completed measures of explicit and implicit Pakistani and English identity, a measure of perceived discrimination, and a measure of paranoia. Perceived discrimination was the strongest predictor of paranoia (0.31). Implicit identities moderated the relationship between perceived discrimination and paranoia (-0.17). The findings suggest that higher levels of implicit Pakistani identity were most protective against high levels of paranoia (0.26, with low implicit English identity; 0.78, with medium English identity; 1.46, with high English identity). Overall, a complex relationship between identity and paranoia was apparent.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".