UNDERSTANDING THE ROLE OF THE ETHNIC DENSITY EFFECT: ISSUES OF ACCULTURATION, DISCRIMINATION AND SOCIAL SUPPORT
Bibliographic record
Abstract
Ecological factors in psychological acculturation research are often neglected, although recent work suggests that context and acculturation may interact in predicting adaptation outcomes. The ethnic density effect–the protective effect related to a greater proportion of people from the same ethnic group living in a particular neighborhood–might be one such ecological candidate. The current study integrates these constructs by unpacking the perceived ethnic density effect and examining how it is related to acculturation in a diverse sample ( N = 146) of immigrant students in Montreal, Canada. It was found that the negative relation between perceived ethnic density and depression was mediated by discrimination but not by social support. Furthermore, a crossover interaction indicated that heritage acculturation was protective against depression for those residing in ethnically concentrated neighborhoods but not for those living in ethnically sparse neighborhoods. This strongly supports an ecology‐acculturation fit, highlighting the need to contextualize acculturation research.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".