MétaCan
Menu
← Back to cohort
Record W4415240349 · doi:10.12927/hcpap.2025.27698

Broadening the Analysis of Canadian Healthcare Reforms

2025· article· en· W4415240349 on OpenAlexvenueaboutno aff
Mark Exworthy, Russell Mannion

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsDecentralizationEquity (law)Health careContext (archaeology)Healthcare systemHealth care reformDimension (graph theory)

Abstract

fetched live from OpenAlex

Analysis of any healthcare reform is complex and multi-faceted. Given the hierarchical levels in health systems (regarding funding and accountability, etc.), a key analytical dimension is between decentralization and centralization. Reforms can be justified on either, often for the same criteria (such as equity or economy). The impact of decentralization/centralization can be assessed by determining "what" is being (de)centralized and from/to whom. This article appraises the analysis of Canadian healthcare reform by Denis, in terms of the TAPIC (Transparency, Accountability, Participation, Integrity and Capability) and decision space frameworks. It draws attention to the importance of incentives, context and implementation in this (and other) reform program.

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)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.702
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.014
Science and technology studies0.0080.008
Scholarly communication0.0100.003
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.000

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 head0.078
GPT teacher head0.310
Teacher spread0.232 · 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 designNot applicable
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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy→Same topicHealthcare Policy and Management→French-language works237,207→