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Record W2905622848 · doi:10.5020/18061230.2018.8802

Health system reforms in mature welfare states: tales from the north

2018· article· en· W2905622848 on OpenAlexaffabout
Jean‐Louis Denis, Susan Usher, Johanne Préval, Élizabeth Côté-Boileau

Bibliographic record

VenueRevista Brasileira em Promoção da saúde · 2018
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsCentre Hospitalier de l’Université de MontréalÉcole Nationale d'Administration PubliqueUniversité de SherbrookeUniversité de Montréal
Fundersnot available
KeywordsTransformative learningCorporate governanceWelfare reformDemocracyGovernment (linguistics)Political scienceHealthcare systemScale (ratio)Welfare stateState (computer science)WelfareHealth policyPublic administrationEconomic growthPublic relationsSociologyHealth careEconomicsPoliticsManagementLaw

Abstract

fetched live from OpenAlex

Objective: This article has the objective show an essay on emerging themes in health system reforms, based on experience in Canada. Data synthesis: Reforms are the privileged mode of social change used by modern democratic societies. Persistent dysfunction and failure to adapt to emerging health needs and priorities within health systems in Canada provide a strong policy rationale to search for alternative strategies that might produce much-needed reforms. Three persistent challenges and opportunities for reform in Canadian health systems are discussed: the design of effective governance arrangements, the large-scale development and implementation of improvement and transformative capacities, and the leadership and engagement of the medical profession in working toward broad system goals. In exploring these challenges, we identify tensions that seem relevant to better understanding health system reform in mature welfare states. Conclusion: Addressing these tensions will require both a reinforcement of state and government capacities and stronger capacities at all levels of the health system to design and support 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.045
GPT teacher head0.380
Teacher spread0.335 · 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 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

Citations1
Published2018
Admission routes2
Has abstractyes

Explore more

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