Conceptualising professionalism in occupational therapy through a <scp>W</scp>estern lens
Bibliographic record
Abstract
INTRODUCTION: The term professionalism is embedded within curriculum and occupational therapy documents, yet, explicit discussion of the concept is lacking in the literature. This paper strives for a greater understanding of how professionalism is currently conceptualised within Western occupational therapy literature. METHODS: A broad literature search was conducted and included international peer-reviewed and grey literature from Western cultures including Australia, Canada, New Zealand, the United Kingdom and the United States. To enrich understanding, some documents from medicine were also included. FINDINGS: Professionalism is widely upheld as a core construct of occupational therapy. However, an evidence-based consensus of the specific elements of professionalism guiding occupational therapy practice is lacking. Currently, understanding of professionalism is largely based on multiple, isolated concepts presented in Western professional association documents. RELEVANCE TO CLINICAL PRACTICE: Acknowledging the multifaceted and multicultural nature of professionalism is essential to begin systematically delineating and conceptualising elements of professionalism specific to occupational therapy. LIMITATIONS: This review has been conducted from a solely Western cultural lens. RECOMMENDATIONS FOR FURTHER RESEARCH: Additional work to highlight differences specific to international contexts, cultures, and societal influences is needed to enrich the understanding of professionalism in occupational therapy practice.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".