Bibliographic record
Abstract
Theories about how knowledge is sought and applied in clinical practice are often referred to as practice epistemologies, and have not been extensively explored in the physiotherapy profession. Tacit assumptions about what counts as physiotherapy knowledge thus form the basis for many approaches to gaining and using information in practice. The purpose of this paper is to propose a physiotherapy practice epistemology, through the notion of the bricoleur, which takes an alternative approach to understanding how knowledge might best be viewed in relation to physiotherapy. The term bricoleur refers to a handyman or handywoman who uses all tools and types of knowledge available. The notion of physiotherapists as bricoleurs recognizes that all practice knowledge is situated within social, cultural, and historical contexts that shape our beliefs about what counts as physiotherapy knowledge. This recognition leads physiotherapists who act as bricoleurs to embrace multiple epistemologies, discovering new ways of knowing and clinical reasoning strategies to provide a more holistic approach to physiotherapy practice. The relationships between expertise in clinical reasoning and the epistemology of the bricoleur are then addressed, explicating the utility of multiple epistemologies in achieving excellent physiotherapy care. A bricoleur's epistemology is then applied to the concept of expertise in physiotherapy, de-stabilizing the notion that a single authoritative approach to the practice of physiotherapy ought to be idealized.
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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 | 0.025 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.005 | 0.074 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.007 | 0.006 |
| 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".