Beyond the art of governmentality: unmasking the distributional consequences of health policies
Bibliographic record
Abstract
The aim of this article is to critique health policy discourses that are taken for granted. This perspective will allow for the identification of 'exclusionary' health policies, which we define as policies that are thought to offer universal benefit, despite yielding adverse effects for significant groups of people in society. As such, policies that are said to be designed 'for all' frequently benefit only a subset of the population. Our intent is to highlight the distributional consequences of certain health policies that are largely institutionalized in contemporary society. We believe that these distributional effects are explicit representations of power in society and that institutions may provide individual 'choice' and 'freedom' that, in turn, yields separation as an outcome, a separating equilibrium. Specifically, if those who benefit from policies of partition are numerous and are to obtain significant advantage or incur limited costs, or if those who are adversely affected are scarce (or hidden), or the size of these adverse effects are small (or perceived to be minor), then partition becomes more likely as a 'legitimate', but exclusionary, instrument of public policy.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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; a candidate call from one teacher head, 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".