Bibliographic record
Abstract
BACKGROUND: Given the nature of occupational therapy philosophy and practice, it is not surprising that "change agent" has been identified as one of the seven professional roles that occupational therapists fulfill. PURPOSE: This Muriel Driver lecture examines the change agent role, what it means, and what knowledge, skills, and personal qualities are necessary to be effective. KEY ISSUES: Overall, relatively little has been written about the change agent role in the occupational therapy literature. Much of what does exist is implicit and often embedded in related topics, such as advocacy. An examination of literature from outside of occupational therapy uncovered four major themes about this role: (a) Change agents are insightful, reflective, and disciplined; (b) Charnge agents are visionary leaders and mobilizers; (c) Change agents are knowledge integrators and translators; and (d) Change agents are diplomatic interventionists who produce meaningful outcomes. These themes point to several areas of silence in the occupational therapy literature. IMPLICATIONS: Overcoming these areas of silence and moving forward will require open, challenging, and scholarly debates; reconsideration of change agent role competencies; and clear messaging that we all have the capacity to be competent and effective change agents regardless of our title or setting.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.131 | 0.038 |
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".