MétaCan
Menu
Back to cohort
Record W2134978339 · doi:10.12927/hcpap..16837

Regionalization in Canada: A Promising Heritage to Build On

2004· letter· en· W2134978339 on OpenAlexaffvenueabout
Jean‐Louis Denis, Damien Contandriopoulos, Marie‐Dominique Beaulieu

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2004
Typeletter
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsLegitimacyHealth careHealthcare deliveryDemocratizationProcess (computing)Order (exchange)BusinessPublic relationsAsset (computer security)Political sciencePoliticsDemocracyComputer science

Abstract

fetched live from OpenAlex

Regionalization has been a major policy experiment in Canadian healthcare. Objectives attached to this policy were ambitious and somewhat unrealistic. Regional health authorities have shown that they can play a useful role in implementing healthcare reform. However, their legitimacy is difficult to sustain, and they need to renew their roles in order to remain a valuable asset in the improvement of healthcare delivery. A model of leadership for RHAs based on content and process dimensions is proposed to support the development of their role in improving the delivery of care. RHAs need to depart from a too distant mode of managing healthcare and support more healthcare organizations in their search for innovative ideas and organizing models and strategies. By adopting such an approach to their roles, it is expected that RHAs will further contribute to the improvement of healthcare and consequently will gain legitimacy to develop more autonomous policies with regard to broad ideals such as democratization and health improvement.

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)0.002
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.926
Threshold uncertainty score0.539

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0180.007
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0180.017
Insufficient payload (model declined to judge)0.0090.001

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 head0.377
Teacher spread0.299 · 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
GenreCommentary

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

Citations9
Published2004
Admission routes3
Has abstractyes

Explore more

Same venueA Nudge Too Far? A Nudge at All? On Paying People to Be HealthySame topicPrimary Care and Health OutcomesFrench-language works237,207