MétaCan
Menu
Back to cohort
Record W4220787407 · doi:10.1177/1470594x221089670

A market failures approach to justice in health

2022· article· en· W4220787407 on OpenAlex
L. Chad Horne, Joseph Heath

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolitics Philosophy & Economics · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRationingHealth careEconomic JusticeMarket failurePublic economicsState (computer science)Distributive justiceIntervention (counseling)Public healthBusinessHealth policyHealth care rationingEconomicsPublic relationsMicroeconomicsPolitical scienceNursingMedicineEconomic growthComputer science

Abstract

fetched live from OpenAlex

It is generally acknowledged that a certain amount of state intervention in health and health care is needed to address the significant market failures in these sectors; however, it is also thought that the primary rationale for state involvement in health must lie elsewhere, for example in an egalitarian commitment to equalizing access to health care for all citizens. This paper argues that a complete theory of justice in health can be derived from a commitment to correcting market failure, or in other words promoting Pareto-efficiency, in the domain of health. This approach can address familiar problems around access to care, as well as problems related to resource allocation and rationing (including resource allocation between generations), the control of health care costs, and the foundations of public health. Egalitarian theories of justice in health cannot make sense of the depth and pervasiveness of state involvement in health and health care; only a theory rooted in the need to correct market failure can.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.077
GPT teacher head0.272
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it