Bibliographic record
Abstract
Rules and principles for guiding decision-making in the health care sector have been debated for decades. Here, we present a critical appraisal of the two most important paradigms in this respect: welfarism and extra-welfarism. While the former deals with the maximization of the overall sum of individual utilities as its primary outcome, the latter has been focusing on the maximization of the overall health status. We argue that welfarism has three main problems: (1) its central idea of overall sum of individual utilities does not capture societal values decisively relevant in the context of health; (2) the use of the Potential Pareto Improvement brings an unresolvable separation between efficiency and equity; and (3) individual utility may not be a good measure in the health sector, given that individuals might value things that diminish their overall health. In turn, the extra-welfarist approach is criticized regarding four main limitations: (1) the advocated expansion of the evaluative space, moving from utility to health, may have represented in reality a narrowing of it; (2) it operates using non-explicit considerations of equity; (3) it still holds the issue of "inability to desire" of unprivileged people being considered the best judges of weighing the criteria used to building the health measures; and (4) there is controversial empirical evidence about society members' values that support its assumptions. Overall, both paradigms show significant weaknesses, but the debate has still been within the realm of welfare economics, and even the new approaches to resource allocation in health care systems appear to be unable to escape from these boundaries.
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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 | 0.069 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.007 | 0.053 |
| Scholarly communication | 0.017 | 0.025 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.011 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 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".