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Public/Private Partnerships for Prescription Drug Coverage: Policy Formulation and Outcomes in Quebec's Universal Drug Insurance Program, with Comparisons to the Medicare Prescription Drug Program in the United States

2007· article· en· W2167152117 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMilbank Quarterly · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsUniversité LavalUniversité de MontréalPierre Elliott Trudeau Foundation
Fundersnot available
KeywordsPrescription drugMedical prescriptionGovernment (linguistics)Principal (computer security)Public administrationModernization theoryPrivate sectorParallelsBusinessPrivate insuranceDrugHealth insurancePolitical scienceMedicineEconomicsLawPharmacologyHealth care

Abstract

fetched live from OpenAlex

In January 1997, the government of Quebec, Canada, implemented a public/private prescription drug program that covered the entire population of the province. Under this program, the public sector collaborates with private insurers to protect all Quebecers from the high cost of drugs. This article outlines the principal features and history of the Quebec plan and draws parallels between the factors that led to its emergence and those that led to the passage of the Medicare Prescription Drug, Improvement and Modernization Act (MMA) in the United States. It also discusses the challenges and similarities of both programs and analyzes Quebec's ten years of experience to identify adjustments that may help U.S. policymakers optimize the MMA.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.062
GPT teacher head0.305
Teacher spread0.242 · 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