MétaCan
Menu
Back to cohort
Record W2792943080 · doi:10.1017/s1744133117000408

Pharmaceutical policy reform in Canada: lessons from history

2018· article· en· W2792943080 on OpenAlexafffundabout
Katherine Boothe

Bibliographic record

VenueHealth Economics Policy and Law · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsMcMaster University
FundersUniversity of TorontoAssociated Medical Services
KeywordsNegotiationEliteUniversal designBusinessPublic economicsPublic administrationPoliticsPolitical scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Canada is the only country with a broad public health system that does not include universal, nationwide coverage for pharmaceuticals. This omission causes real hardship to those Canadians who are not well-served by the existing patchwork of limited provincial plans and private insurance. It also represents significant forgone benefits in terms of governments' ability to negotiate drug prices, make expensive new drugs available to patients on an equitable basis, and provide integrated health services regardless of therapy type or location. This paper examines Canada's historical failure to adopt universal pharmaceutical insurance on a national basis, with particular emphasis on the role of public and elite ideas about its supposed lack of affordability. This legacy provides novel lessons about the barriers to reform and potential methods for overcoming them. The paper argues that reform is most likely to be successful if it explicitly addresses entrenched ideas about pharmacare's affordability and its place in the health system. Reform is also more likely to achieve universal coverage if it is radical, addressing various components of an effective pharmaceutical program simultaneously. In this case, an incremental approach is likely to fail because it will not allow governments to contain costs and realize the social benefits that come along with a universal program, and because it means forgoing the current promising conditions for achieving real change.

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 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 score0.924
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.129
GPT teacher head0.342
Teacher spread0.213 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations4
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueHealth Economics Policy and LawSame topicHealthcare Policy and ManagementFrench-language works237,207