Global migration: Moral, political and mental health challenges
Bibliographic record
Abstract
Global migration is expected to continue to increase as climate change, conflict and economic disparities continue to challenge peoples' lives. The political response to migration is a social determinant of mental health. Despite the potential benefits of migration, many migrants and refugees face significant challenges after they resettle. The papers collected in this thematic issue of Transcultural Psychiatry explore the experience of migration and highlight some of the challenges that governments and healthcare services need to address to facilitate the social integration and mental health of migrants. Clinicians need training and resources to work effectively with migrants, focusing on their resilience and on long-term adaptive processes. Efforts to counter the systemic discrimination and structural violence that migrants often face need to be broad-based, unified, and persistent to make meaningful change. When migrants are free to realize their talents and aspirations, they can help build local communities and societies that value diversity.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.022 | 0.030 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".