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Hospital restructuring in smaller urban Ontario settings: unwritten rules and uncertain relations

2001· article· en· W2040195534 on OpenAlexaffvenueabout
Neil Hanlon

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsRestructuringMetropolitan areaContext (archaeology)WelfareBusinessSocial WelfareService delivery frameworkPublic administrationScale (ratio)Order (exchange)Social securityHealth careService (business)Public relationsPolitical scienceEconomic growthEconomicsMedicineFinanceMarketingLaw

Abstract

fetched live from OpenAlex

Important changes are underway in the management and provision of welfare service activities in advanced capitalist societies as governments scale back their responsibilities and commitments to social security and health care. In order to understand the processes by which the reform imperatives of the central state are implemented at the local level, it is necessary to account for particular organizational and place‐based contingencies which influence decision making and strategic response. This paper presents a framework for understanding the context of executive decision making in the human services sector and uses the framework to illustrate issues of locally designed hospital restructuring in smaller urban centres in the province of Ontario, Canada. Specific experiences of the Chief Executive Officers of two non‐metropolitan hospital settings are examined to explore the unwritten rules of hospital conduct and the relations of uncertainty that characterize efforts to restructure hospital services through formal arrangements with other independently governed hospitals and health care delivery organizations.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.239
Teacher spread0.223 · 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

Citations19
Published2001
Admission routes3
Has abstractyes

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