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Record W1964718192 · doi:10.1016/j.hcmf.2011.08.004

Bridging the Gap between Family Doctors and Regional Health Authorities

2011· article· en· W1964718192 on OpenAlexaffabout
Lydia Hatcher, Oscar Howell

Bibliographic record

VenueHealthcare Management Forum · 2011
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBridging (networking)Health careBusinessFamily doctorsCommunity healthFamily healthPublic relationsNursingFamily medicinePublic administrationMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

The communication between family doctors and regional health authorities has become more complex and fragmented over the last 2 decades. By using a novel approach, we developed a medical advisory committee structure for community physicians enshrined in the regional health authority bylaws. This has improved bilateral communication, policy making that affects patients in the community, linkages between programs and family doctors, and input into the institutional care of our patients. We believe this model could be implemented or adapted by regional health authorities elsewhere in Canada having as its ultimate goal better patient care.

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)0.030
metaresearch head score (Gemma)0.064
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 score0.042
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.064
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.006
Scholarly communication0.0070.006
Open science0.0020.015
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0240.002

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 head0.221
GPT teacher head0.423
Teacher spread0.203 · 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

Citations1
Published2011
Admission routes2
Has abstractyes

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