The hierarchy of evidence in advanced wound care: The social organization of limitations in knowledge
Bibliographic record
Abstract
In this article, we discuss how we used institutional ethnography (Institutional ethnography as practice, Rowman & Littlefield, Lanham, MD and 2006) to map out powerful ruling relations that organize nurses' wound care work. In recent years, the growing number of people living with wounds that heal slowly or not at all has presented substantial challenges for those managing the demands on Canada's publicly insured health-care system. In efforts to address this burden, Canadian health-care administrators and policy-makers rely on scientific evidence about how wounds heal and what treatments are most effective. Advanced wound care exemplifies the growing authorization of particular forms of evidence that change the ways in which nurses come to know about and conduct their work. The focus of this paper's nursing inquiry is a critique of registered nurses' wound work as it arises within the established uptake of scientific evidence.
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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 | 0.216 | 0.322 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.026 | 0.015 |
| Science and technology studies | 0.027 | 0.183 |
| Scholarly communication | 0.029 | 0.041 |
| Open science | 0.006 | 0.031 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".