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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 OpenAlexaffabout
Marie‐Pascale Pomey, Pierre‐Gerlier Forest, Howard A. Palley, Élisabeth Martin

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.617

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.002
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations48
Published2007
Admission routes2
Has abstractyes

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