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Record W2167210268 · doi:10.1093/jmp/jhn025

Public Health Insurance under a Nonbenevolent State

2008· article· en· W2167210268 on OpenAlex
Pierre Lemieux

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

VenueThe Journal of Medicine and Philosophy A Forum for Bioethics and Philosophy of Medicine · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsBioethicsPublic healthState (computer science)Library sciencePhilosophy of medicinePolitical scienceSocial scienceSociologyMedicineAlternative medicineLawNursingMathematics

Abstract

fetched live from OpenAlex

This paper explores the consequences of the oft ignored fact that public health insurance must actually be supplied by the state. Depending how the state is modeled, different health insurance outcomes are expected. The benevolent model of the state does not account for many actual features of public health insurance systems. One alternative is to use a standard public choice model, where state action is determined by interaction between self-interested actors. Another alternative--related to a strand in public choice theory--is to model the state as Leviathan. Interestingly, some proponents of public health insurance use an implicit Leviathan model, but not consistently. The Leviathan model of the state explains many features of public health insurance: its uncontrolled growth, its tendency toward monopoly, its capacity to buy trust and loyalty from the common people, its surveillance ability, its controlling nature, and even the persistence of its inefficiencies and waiting lines.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.333
GPT teacher head0.350
Teacher spread0.017 · 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