MétaCan
Menu
Back to cohort

Rebalancing health systems toward community-based care: The role of subsectoral politics

2018· article· en· W2893629992 on OpenAlexafffundabout
Allie Peckham, Frances Morton-Chang, A. Paul Williams, Fiona A. Miller

Bibliographic record

VenueHealth Policy · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsPoliticsPolitical scienceHealth careSociologyPublic administrationMedicineLaw

Abstract

fetched live from OpenAlex

There has been increased policy discourse urging a "rebalancing" of health systems from institutionally-based to community-based approaches. This paper offers an analysis of the subsectoral dynamics that condition opportunities to strengthen community-based care relative to acute care. We report on the results of a policy study in Ontario, Canada that explored factors impacting on the capacity to expand community-based care. In so doing, we highlight the challenges associated with the community subsector's ability to develop 'critical' status and challenge the dominance of the acute subsector. We conclude that attempts to rebalance health systems toward community-based care should begin by understanding that health care is not a monolithic policy sector, but rather a collection of proximate policy sub-sectors, inclusive of community care, acute care, and institutional care, each with their own internal characteristics and dynamics that impact sectoral directions.

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)0.012
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.371

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.011
Scholarly communication0.0140.005
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.110
GPT teacher head0.356
Teacher spread0.246 · 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 designQualitative
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

Citations16
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueHealth PolicySame topicHealthcare Policy and ManagementFrench-language works237,207