Bibliographic record
Abstract
In 'Equity in health care: the Irish perspective', Smith and Normand present a fascinating exercise in forensic economics investigating equity in the Irish health system.What, they ask, is the guiding equity definition, or principle, for the Irish health care system?To find out, they examine both stated preferencesthe equity principles espoused in recent Irish health policy documentsand revealed preferencescrucial features in the design of the Irish health care system.Their main findings won't surprise anyone who has been involved in health policy very long.Even in the health policy documents alone, rather than a single guiding equity principle, they find a confusing mix of conflicting equity definitions: "This analysis of one country's policy commitment on equity outlines an unclear, inconsistent and varied definition, … at one point, the strategy is concerned with equality in access and opportunity (to achieve full health potential), at another it is concerned with equality in health status, and at yet another it is concerned with distribution of resources according to need" (Smith and Normand, 2011: 211).Moreover, they find a health care system that, in many respects, is incongruent with the articulated definitions (e.g.high rates of cost sharing that inhibits access to needed care).At least with respect to equity, Irish health policy is rife with irrationality, prompting Smith and Normand to offer the Irish system as a cautionary tale for other countries.One suspects, however, that many other countries would fare little better under such scrutiny.The precise nature of the irrationalities and inconsistencies would differ, but they would no doubt be present.There are, of course, many reasons for the inconsistencies that Smith and Normand discover, especially those between the stated equity definitions and the actual system design.At any point in time a system design reflects an amalgam of historical decisions made in varying contexts by different governments that pursued differing equity objectives.Any single government cannot simply
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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 | 0.018 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.039 |
| Scholarly communication | 0.021 | 0.020 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.011 | 0.023 |
| Insufficient payload (model declined to judge) | 0.010 | 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".