Global perspectives on migration and forced displacement: Theory, research, and practices for enacting an occupation-based approach
Bibliographic record
Abstract
This commentary reports on the international dialogic session delivered at the inaugural World Occupational Science Conference in Vancouver (2022) and a subsequent pre-congress workshop held at the World Federation of Occupational Therapists congress in Paris (2022). Global estimates of migration are at an all-time high, with forced migrants accounting for a staggering number, representing approximately 1% of the global population (Migration Policy Institute, Citation2022). Occupational scientists and therapists can make a significant contribution to developing knowledge and supporting action to address the numerous occupational implications of migration. Ongoing dialogue within occupational science and therapy is required to help ensure that; 1) theoretical bases are relevant, 2) ethical and methodologically collaborative robust research is conducted, and 3) the knowledge and skills necessary for working with migrants and addressing systemic barriers to occupational participation are being developed and shared by occupational scientists within the occupational therapy community.
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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 | 0.021 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.068 |
| Scholarly communication | 0.013 | 0.023 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".