Teaching and Evaluating an Occupational Perspective in Canada: A Descriptive Qualitative Study
Bibliographic record
Abstract
Background. Occupation is the core domain of occupational therapy, and an occupational perspective is foundational for practice. Research has explored how an occupational perspective is taught. Yet, little has explored the Canadian occupational therapy educational context. There are national differences in core competencies and accreditation standards and nuances in how occupation is defined and what conceptual models are used. As such, a Canadian perspective may offer new understandings of value both within and outside of Canada. Purpose. To understand how, in Canada, educators teach and evaluate student occupational perspectives in entry-level master of occupational therapy programs. Method. This study used a descriptive qualitative design with an interpretive approach. Semi-structured interviews were used to gather data from 12 educators from Canadian entry-level occupational therapy programs. Reflexive thematic analysis was used for data analysis. Findings. Five themes were identified: (1) occupational perspectives as pedagogy (2) it's a process, not an end state; (3) “everybody is involved”: a community of educators; (4) thinking critically; and (5) “hard to evaluate.” Conclusion. The complex, dynamic, and contextualized nature of an occupational perspective calls for critical, reflexive, communal, and innovative pedagogical and assessment approaches.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.036 | 0.016 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".