New Public Management and Hybridity in Healthcare: The Solution or the Problem?
Bibliographic record
Abstract
The research aim of this chapter is to understand how different institutional logics affect the day-to-day activities of healthcare providers and whether the cohabitation of professional logics with business-like logics increases medical providers’ effectiveness and gives chance to constrain healthcare costs. This research is based on longitudinal case study about the restructuring of the Canadian healthcare system in Alberta in 1992–2008, described in two papers (Reay & Hinings, 2005, 2009). We identify the situation after encroachment of a new, business-like logic into a healthcare system as more complex than described in the extant literature. We challenge the findings of the case study authors that there are two cohabitating logics in healthcare: the business-like logic supported by the government and the logic of medical professionalism. From our research it appears that there are two other logics: a managerial logic derived from business-like logic, and a hybrid professional logic that is a modification of the logic of medical professionalism. Across the healthcare field in general, business-like logic has been competing with the logic of medical professionalism, but on the medical providers’ level these logics become uncoupled. Within a medical provider, on the external, symbolic layer, physicians follow their professional logic and managers show conformity with governmental principles. But on the backstage layer, where the day-to-day work is actually performed, these two logics are subject to modification, creating a space for compromise and cooperation, leading to a growth of the number of unnecessary medical services preventing cost containments in healthcare.
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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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.051 |
| Scholarly communication | 0.021 | 0.037 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".