Roemer 20 Years Later: When a Classical Health-System Typology Meets Market-Oriented Reforms
Bibliographic record
Abstract
In 1990, Roemer came up with a very influential health system typology. From his vast study, emerged three types of health care systems: nationalized, mandated and entrepreneurial. Health care systems are not static; slow changes and reforms somewhat alter values and goals on which those systems were initially established. It is fair to say, then, that over the last two decades, health care reformers have adopted a market-oriented governance model that blends new public management (NPM) and managed competition reforms in the provision of health care services to transform supply- and demand-side actors into “responsibilized” customers, payers or providers. These transformations beg the question as to whether we are witnessing a radical redefinition of health care systems through the implementation of market-oriented governance. We propose to add the evolution of market-oriented health reforms in five case studies to Milton Roemer’s typology of health systems. In light of our findings, we will wrap up the analysis with an assessment of the usefulness of Roemer’s classification for social scientists to grasp the evolution of health systems over the past 20 years, and more importantly, to analyze the current state of these health care systems after years of market-oriented reforms.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.008 | 0.019 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".