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Record W1989878121 · doi:10.12927/hcpol.2013.23207

Rural Health Services: Finding the Light at the End of the Tunnel

2013· article· en· W1989878121 on OpenAlexaffvenueabout
Stefan Grzybowski, Jude Kornelsen

Bibliographic record

VenueHealthcare policy · 2013
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStaffingBusinessHealth careSustainabilityNursingHealth servicesCatchment areaService (business)Rural areaPopulationPublic relationsEnvironmental planningMedicineGeographyEnvironmental healthEconomic growthPolitical scienceMarketingDrainage basin

Abstract

fetched live from OpenAlex

Many rural communities across canada are facing challenges to the sustainability of core emergency and acute care health services, primarily due to problems with medical and nursing staffing. Data related to service efficacy and effectiveness are not well organized. Most of Canada still relies on reporting by large geopolitical areas (local health areas) that do not always relate natural catchment population outcomes to community hospital services. Re-organizing rural health services' outcome reporting by the characteristics of geographically defined catchment populations would facilitate better planning, systemic quality improvement and stronger continuing professional development for health professionals. It may also serve to inform the transformation of core health services in larger communities.

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)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.408
Threshold uncertainty score0.811

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.007
Scholarly communication0.0100.006
Open science0.0020.006
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0150.002

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 head0.045
GPT teacher head0.431
Teacher spread0.386 · 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 designNot applicable
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

Citations13
Published2013
Admission routes3
Has abstractyes

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