MétaCan
Menu
Back to cohort
Record W308330426

The Newfoundland and Labrador Heart Health Program dissemination story: the formation and functioning of effective coalitions.

2001· article· en· W308330426 on OpenAlexaboutno aff
Pablo Holmes, Doreen Neville, Catherine Donovan, Clayton MacDonald

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsnot available
Fundersnot available
KeywordsFishingUnemploymentPopulationCommunity healthGeographyClosure (psychology)Economic growthBusinessPolitical scienceHealth careEnvironmental healthMedicineEconomics
DOInot available

Abstract

fetched live from OpenAlex

Newfoundland and Labrador is the most easterly province of Canada (O'Loughlin et al., Figure 1) with a population of 537,000. Rural in nature, 50% of the population resides in widely-dispersed communities of less than 2500 people. The economy traditionally relied on the fishing industry, but with the closure of the once lucrative cod fishery in 1991, the poorest province in Canada faced a difficult economic climate with up to 20% unemployment rates. With little funding available to supplement or sustain expensive initiatives, the Demonstration Phase of the Newfoundland and Labrador Heart Health Program (1990-1996) focused on how community-based programs are developed and sustained, with a view to diffusion throughout the province. The whole province was defined as the demonstration site for the project, and a community mobilization strategy was used with extensive reliance on community health professionals and volunteer contributions.

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)0.046
metaresearch head score (Gemma)0.054
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 score0.349
Threshold uncertainty score0.702

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0240.016
Scholarly communication0.0170.012
Open science0.0030.012
Research integrity0.0110.016
Insufficient payload (model declined to judge)0.0100.001

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 head0.178
GPT teacher head0.540
Teacher spread0.362 · 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

Citations2
Published2001
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicHealth Policy Implementation ScienceFrench-language works237,207