Role Emerging Placements: Skills Development, Postgraduate Employment, and Career Pathways
Bibliographic record
Abstract
Occupational therapy educators are increasingly using role emerging placements (REPs) as a forum for students to develop skills required to work in emerging areas of practice. This study explores the impact of REPs on skill development, postgraduate employment, and career pathways for occupational therapists. An online survey was sent to occupational therapists across Canada (n = 1,763). Occupational therapists who had completed a REP responded to the online survey (n = 88). Descriptive analysis was used to examine trends in the quantitative data, and content analysis was used to code categories derived from qualitative survey data. Results indicated five skills that developed in REPs and were used throughout an occupational therapist’s career. REPs appeared to have no impact on choice of practice field postgraduation, career pathways, or employment status. However, a group who identified their current job titles other than occupational therapy indicated a positive experience regarding their skills, career pathways, and employment status. Study results highlight the need to further understand the experiences of graduates in their REPs and the factors in REPs that may influence the career trajectory of occupational therapists.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".