Exploring the integration of internationally educated occupational therapists into the workforce
Bibliographic record
Abstract
BACKGROUND: British Columbia (BC) is a popular Canadian work destination for occupational therapists from around the world. PURPOSE: This study explored the experiences of stakeholders involved in the integration of internationally educated occupational therapists (IEOTs) into the BC workforce. METHOD: Semi-structured interviews were conducted with the three primary stakeholder groups (40 IEOTs, 12 supervising occupational therapists, seven managers), as well as with seven key informants. Participants were purposively sampled and thematic analysis was applied to the data. FINDINGS: Three themes were identified that fit sequentially along a workforce-integration continuum: "coming to Canada," "registering with the college," and "integrating into the workplace." Within those themes, findings were organized into two categories, "ingredients for success" and "stumbling block," and multiple subcategories. IMPLICATIONS: The findings suggest that hiring IEOTs can bring benefits to the workplace and clients. However, changes made along the continuum would facilitate workforce integration, ultimately benefiting all stakeholders. These findings may be of interest to IEOTs, occupational therapists, and managers as well as individuals working in regulation and policy.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".