Public Good, or Goods for the Public: The Commercialization of Academic Health Research
Bibliographic record
Abstract
In Health Matters, contributors from a range of disciplinary and interdisciplinary traditions address multiple dimensions of health care, such as nursing, midwifery, home care, pharmaceuticals, medical education, and palliative care. Through their explorations, the book poses questions about the role that the forms of expertise associated with evidence-based health care play in shaping how we understand and organize health services. Authors critique instrumental, managerial ways of knowing health care and focus on how such ways of knowing limit our understandings of and responses to health care problems and are linked with the growing commodification, individualization, and privatization of Canadian health services. Working with analytic perspectives such as feminism, Marxist political economy, critical ethnography, science and technology studies, governmentality studies, and institutional ethnography, the volume demonstrates how critical social science perspectives contribute alternative perspectives about what counts as health care problems and how to best to address them.
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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 | 0.038 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.012 | 0.072 |
| Scholarly communication | 0.045 | 0.037 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".