Democratizing and Professionalizing Risk Work: The Institutional Work of Hospital Risk Managers
Bibliographic record
Abstract
This paper seeks to better understand the way hospital risk managers work at the institutionalization of risk management by examining how they draw upon their risk-related practices as a basis for institutional change. From an inductive study of hospital risk managers in the Quebec healthcare sector, we provide a situated account of the institutionalization of the practices that risk managers deploy at the organizational and field levels. More specifically, our results show that their practices form two broader recursive forms of institutional work, namely democratizating risk work at the intra-organizational level and professionalizing risk work at the extra-organizational level. We argue that their recursive relationship demonstrates how the risk work done at one level facilitates the risk work done at the other. The paper ends by discussing the importance of gaining a better understanding of how the risk manager role and its institutional work are linked together.
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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 | 0.034 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.050 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| 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".