Evidence-Based Medicine: Ambivalent Reading and the Clinical Recontextualization of Science
Bibliographic record
Abstract
This article contributes to the investigation of evidence-based medicine (EBM) as text-mediated relations of governance. Social critiques of EBM typically rely on a negative conception of power, such that EBM is considered to contain or limit the scope of medical practice. This article, by contrast, explores EBM as a productive relation, one that governs through medicine's `freedom' and opens up spaces of intervention. The article draws on an institutional ethnographic study of a research transfer initiative called informed - an evidence-based newsletter for family physicians. My investigation of the work practices of making informed underscores how texts are fundamental to the social organization of EBM. Through the example of informed, I locate reading as a central object of governance within EBM. I emphasize how the problematization of physicians as indifferent readers is linked with an effort to intervene in medical work through a new kind of text that clinically recontextualizes biomedical science.
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 | 0.045 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.009 | 0.153 |
| Scholarly communication | 0.024 | 0.020 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".