Acculturation Strategies and its Effect on Depressive Symptoms in the Brazilian Immigrant Community in the Greater Toronto Area
Bibliographic record
Abstract
Among several difficulties associated with immigration, acculturation process has been\nrecognized as one of the main stressors and one of the major risk factors associated in the\nincidence of mental disorders. The strategies adopted by individuals to deal with the\nacculturation process appear to be predictive of different mental health outcomes. This\nexploratory study investigated the relationship between acculturation strategies and the\noccurrence of symptoms of depression in the context of the Brazilian immigrant community\nliving in the Greater Toronto Area. The results demonstrated that Separation and Assimilation\nwere the predominant strategies for this sample and that acculturation strategies failed to serve as\nsignificant predictors of depression scores. However, participants with Separation as their\npredominant acculturation strategy exhibited higher depressive symptom endorsement. The\nsignificance of these findings in the context of previous research as well as its implications for\nfuture research and critical multicultural practice in mental health 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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".