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Healthcare reforms, inertia polarization and group influence

2018· article· en· W2883675950 on OpenAlexafffundabout
Damien Contandriopoulos, Astrid Brousselle, Catherine Larouche, Mylaine Breton, Michèle Rivard, Marie‐Dominique Beaulieu, Jeannie Haggerty, Geneviève Champagne, Mélanie Perroux

Bibliographic record

VenueHealth Policy · 2018
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsSt Mary's HospitalThe Quebec Population Health Research NetworkUniversity of VictoriaMcGill UniversityHôpital Charles-Le MoyneUniversité de SherbrookeUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsVetoHealth careHealth policyPublic relationsPublic economicsFocus groupSociologyPoliticsPolitical sciencePublic administrationEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Healthcare systems performance is the focus of intense policy and media attention in most countries. Quebec (Canada) is no exception, where successive governments have struggled for decades with apparently intractable problems in care accessibility overall, poor performance, and rising costs. This article explores the underlying causes of the disconnection between the high salience of healthcare system dysfunctions in both media and policy debates and the lack of policy change likely to remedy those dysfunctions. Academically, public policies' evolution is usually conceptualized as the product of complex, long-term interactions among diverse groups with specific power sources and preferences. In this context, we wanted to examine empirically whether divergences in stakeholders' views concerning various healthcare reform options could explain why certain policy changes are not implemented despite consensus on their programmatic coherence. The research design was an exploratory sequential design. Data were analyzed narratively as well as graphically using a method derived from social network analysis and graph theory. Results showed striking intergroup convergence around a programmatically sound policy package centred on the general objective of strengthening primary care delivery capacities. Those results, interpreted in light of political science elitist perspectives on the policy process, suggest that the incapacity to reform the system might be explained by one or two groups' having a de facto veto in policy-making.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.350
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.479
Teacher spread0.427 · 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
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

Citations11
Published2018
Admission routes3
Has abstractyes

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