The changing contours of experimental governance in European health care
Bibliographic record
Abstract
For over a decade, beginning in the late 1990s, discussion over softer modes of governance animated academic scholarship in the fields of law, politics, and public policy. This debate was especially pronounced in Europe. Since the late 2000s, however, discussion of this approach has declined precipitously. Is the "soft governance" model dead? Or, more precisely, has the economic crisis killed it? This article argues that, to the contrary, the EU's austerity measures have made softer governance more relevant in two quite distinct ways. Administratively, new mechanisms of health policy coordination are able to provide policy solutions in a much more effective way than could more formal and rigid forms of legal harmonisation. Politically, it establishes a normative perspective which unifies actors across a number of administrative units and challenges the dominant ideological force of the market-based principles upon which the EU's austerity policies are constructed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".