Effects of Workplace Policy on Continuing Professional Development: The Case of Occupational Therapy in Nova Scotia, Canada
Bibliographic record
Abstract
BACKGROUND: Continuing professional development is essential for professionals to remain competent, and for effective recruitment and retention. PURPOSE: This paper reports a qualitative study of the effects of workplace policy on continuing professional development on a small, dispersed profession in a resource-challenged province, using the case example of occupational therapy in Nova Scotia. METHODS: The study used a multi-methods design, theoretically based on institutional ethnography. Methods were critical appraisal of the literature, interview and focus group data collection with 28 occupational therapists and 4 health services administrators, and a review of workplace policy. RESULTS: The study identified a policy wall. Notable policies were those which defined who is responsible for continuing professional development, and which limited employee benefits and work flexibility options for those with family duties. It appears that a female-dominated profession, such as occupational therapy, may also face gender-based challenges. PRACTICE IMPLICATIONS: Suggestions are offered for workplace policy makers, unions, provincial regulatory organizations, and health professionals. The findings are generally applicable to any small, dispersed health profession operating in resource-challenged conditions.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".