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Record W2914956142 · doi:10.12927/hcq.2018.25702

Integrating Care in Scotland

2018· article· en· W2914956142 on OpenAlexafffundvenueabout
Cathy Fooks, Jodeme Goldhar, Walter P. Wodchis, G. Ross Baker, Jane Coutts

Bibliographic record

VenueHealthcare Quarterly · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsCanadian Foundation for Healthcare ImprovementCARE Canada
FundersUniversity of Toronto
KeywordsSocial careHealth careFoundation (evidence)Best practiceHealth servicesManagementService (business)Public relationsNursingPublic administrationPolitical scienceMedicineBusinessMarketingLawEnvironmental healthEconomics

Abstract

fetched live from OpenAlex

This issue of Healthcare Quarterly includes the second of a three-part series developed by Ontario's The Change Foundation featuring international perspectives on health service delivery models that improve system integration and ensure seamless services and better coordination. Part 1 featured Chris Ham, chief executive of the London-based King's Fund think tank. In this issue, Geoff Huggins, director for Health and Social Care Integration in Scotland, discusses Scotland's experience and lessons learned after legislating integrated health and social care in 2015.

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)0.006
metaresearch head score (Gemma)0.015
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: none
Teacher disagreement score0.111
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0100.004
Scholarly communication0.0120.006
Open science0.0020.011
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0190.002

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 head0.047
GPT teacher head0.400
Teacher spread0.353 · 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

Citations7
Published2018
Admission routes4
Has abstractyes

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