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Record W1971503382 · doi:10.1186/1617-9625-5-12

Building research capacity for evidence-informed tobacco control in Canada: a case description

2009· article· en· W1971503382 on OpenAlexafffundabout
Paul McDonald, Sarah Viehbeck, Sarah Robinson, Scott T. Leatherdale, Candace I. J. Nykiforuk, Mari Alice Jolin

Bibliographic record

VenueTobacco Induced Diseases · 2009
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of AlbertaCancer Care OntarioUniversity of TorontoMcMaster UniversityUniversity of Waterloo
FundersCancer Care Ontario
KeywordsTobacco controlFamily medicineControl (management)Alternative medicineMedicinePublic healthEnvironmental healthNursingComputer scienceArtificial intelligencePathology

Abstract

fetched live from OpenAlex

Tobacco use remains the leading cause of death and disability in Canada. Insufficient research capacity can inhibit evidence-informed decision making for tobacco control. This paper outlines a Canadian project to build research capacity, defined as a community's ability to produce research that adequately informs practice, policy, and future research in a timely, practical manner. A key component is that individuals and teams within the community must mutually engage around common, collectively negotiated goals to address specific practices, policies or programs of research. An organizing framework, a set of activities to build strategic recruitment, productivity tools, and procedures for enhancing social capital are described. Actions are intended to facilitate better alignment between research and the priorities of policy developers and service providers, enhance the external validity of the work performed, and reduce the time required to inform policy and practice.

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 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)0.003
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.759
GPT teacher head0.656
Teacher spread0.103 · 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 teacher head, not a consensus.

Study designObservational
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

Citations11
Published2009
Admission routes3
Has abstractyes

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