Models of professional regulation: institutionalizing an agency relationship
Bibliographic record
Abstract
The regulation of medical practice can historically be understood as a second-level agency relationship whereby the state delegated authority to professional bodies to police the primary agency relationship between the individual physician and the patient. Borow, Levi and Glekin show how different national systems vary in the degree to which they insist on institutionally insulating the agency function from the promotion of private professional interests, and relate these variations to different models of the health care state. In fact these differences have even deeper roots in different "liberal" or "coordinated" varieties of capitalist political economies. Neither model is inherently more efficient than the other: what matters is the internal coherence or logic of these systems that conditions the expectations of actors in responding to particular challenges. The territory that Borow, Levi and Glekin have usefully mapped invites further exploration in this regard.This is a commentary on http://www.ijhpr.org/content/2/1/8.
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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.040 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.027 | 0.032 |
| Insufficient payload (model declined to judge) | 0.003 | 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".