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Record W2530636186 · doi:10.1177/0840470416658903

Four persistent rural healthcare challenges

2016· review· en· W2530636186 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealthcare Management Forum · 2016
Typereview
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsRegional Municipality of Durham
Fundersnot available
KeywordsDemographicsHealth careHealth professionalsRural areaRural populationHealthcare systemPopulationPublic relationsEconomic growthPolitical scienceMedicineSociologyEnvironmental health

Abstract

fetched live from OpenAlex

Today, 25% of Canadians live in rural and remote parts of Canada. The evidence is that these Canadians do not enjoy the same health status as citizens living in more urban settings. This article explores four persistent healthcare challenges: population demographics, place, professionals, and public participation. By exploring solutions that some rural communities have used to address these challenges, this article aims to provide insights into lessons that have been learned that they may be considered and potentially applied to both rural and urban environments in the interest of better healthcare for all.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.760
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0010.010

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 head0.182
GPT teacher head0.472
Teacher spread0.290 · 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