Bibliographic record
Abstract
Models provide a framework for thinking and clinical decision making. They make explicit the profession’s scope of concern (and, therefore, role) and how it identifies and understands issues and problems, and they provide a structure for systematic and comprehensive practice ( Turpin & Iwama, 2011 ) that guides notions of appropriate evaluation and intervention strategies and ways of evaluating outcomes. A number of occupational therapy models of practice have been developed over the years that assist occupational therapists in understanding the difficulties individuals are experiencing and the factors that contribute to them. Each model of practice conceptualizes the person, occupation or performance, environment, and interaction between these in different ways, all of which have an impact on how occupational therapists engage with issues and implement occupational and environmental interventions. This chapter reviews four key approaches used by occupational therapists when undertaking home modifications and examines how each shapes home modification practice and outcomes. The chapter describes the rehabilitation model, Canadian Model of Occupational Performance and Enablement (CMOP-E), ecological occupational therapy models, and Kawa model and examines how each contributes to our understanding of how people engage in meaningful occupations in the home and community. Also examined is the evolution of occupational therapy practice models and their relevance and integrity in light of politico-sociocultural trends, such as the shift to a social model of disability and the development of client-driven services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".