The Community Development Progress and Evaluation Tool: Assessing community development fieldwork / Un outil pour évaluer les stages en développement communautaire: Le Community Development Progress and Evaluation Tool
Bibliographic record
Abstract
BACKGROUND: Both the Canadian Association of Occupational Therapists (CAOT) and World Federation of Occupational Therapists (WFOT) fieldwork guidelines promote fieldwork experiences that build community capacity. Yet, no existing tool that assesses the unique skills of community development fieldwork could be identified within or outside of occupational therapy. PURPOSE: This article describes the development of the Community Development Progress and Evaluation Tool (CD-PET), an assessment of community development fieldwork in occupational therapy. TOOL DEVELOPMENT: The CD-PET was developed in five distinct phases: (a) literature review, (b) identification of a theoretical framework, (c) tool construction, (d) pilot testing, and (e) ongoing refinement. Focus groups yielded input from preceptors and students. Once developed, the assessment was pilot tested with feedback received through an online survey completed by preceptors and students. Key enablement skills identified in Enabling Occupation II provided the foundation for the tool. IMPLICATION: The CD-PET is a student assessment and learning tool for occupational therapy students and preceptors that supports learning in the key enablement skills that are used in community development fieldwork.
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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 | 0.049 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".