Cultural Identity, Acculturation and Mental Health off Immigrant Youths - Review Study for Canada’s Immigrant Youth Population
Bibliographic record
Abstract
Purpose: This study presents the finding of various research project examining relationship between cultural identity, acculturation, and mental health, and suggested the health policy making for Canada's immigrant population based on these findings. Methods: Research objectives were accomplished by conducting a literature review. The main areas of the literature review included immigration and mental health outcomes, cultural identity, acculturation and changes in psychological well-being. Results: Arrival and resettlement in a new country often involves a period of significant readjustment and stress. Findings from previous studies suggest that cultural identity may contribute uniquely to the psychological well-being and successful development of ethnic-minority youths. It has been proposed that acculturation also affects mental health by virtue of being a source of stress, or by affecting individual responses to stress. Conclusion: This study concluded with policy implications and recommendation for future study. From the review of relevant literatures, the author suggests that programs and policies that empower immigrant groups to develop and maintain their own cultural identity and ethnic pride have positive long-term effects for the improvement of immigrant population's mental health status.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 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".