Use of Measuring Tools in Practice Development Projects: A Critical Perspective
Bibliographic record
Abstract
BACKGROUND.: Occupational therapists are generally positive towards use of measuring tools. However, such use may be problematic. PURPOSE.: To illuminate hidden and adverse effects of using measuring tools in occupational therapy. METHOD.: A Foucauldian inspired thematic analysis of the use of measuring tools in 13 reports of practice development projects in Denmark. FINDINGS.: Three themes were constructed: "Categorisation of loss", "Conduct of conduct: Self-tracking and competition", and "Conforming to expected forms of everyday living". Measuring tools tended to produce generalised truths about older adults and were used to predict outcome of or access to reablement programs. The measurements guided both older people and professionals, and measurements created both motivation and resistance. The tools served as an extension of the healthcare professionals' authority. IMPLICATIONS.: When appropriately situated, measuring tools have the potential to empower and enhance older adults' lives and should be the focus of greater clinical attention.
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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 | 0.324 | 0.326 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.024 | 0.069 |
| Scholarly communication | 0.029 | 0.029 |
| Open science | 0.007 | 0.023 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.001 | 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".