Research-Based Recommendations for Supporting Forced Migrant Elite Athletes in Their Cultural Transitions to Canada
Bibliographic record
Abstract
Growing pathways exist for forced migrant elite athletes to continue sport within host countries’ sports systems following forced migrations. These pathways provide relocation opportunities but remain limited in supporting these athletes’ cultural transitions and integration post-settlement. Drawing on a funded project conducted with 14 forced migrant elite athletes, the purpose of this manuscript was to translate empirical findings on forced migrant elite athletes’ cultural transitions into recommendations for SPPs to support athletes’ adaptation needs. We first introduce how guided tours facilitate trusting athlete-practitioner relationships. We follow with introducing an arts-based method to develop awareness of athletes’ transition demands and their inner resources for overcoming these. We conclude with highlighting the importance of finding meaning following migration as a transition. These recommendations promote individual adaptability, well-being, purpose, social integration, and growth.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".