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Record W1970620442 · doi:10.1136/tc.2006.017244

Building the evidence base for effective tobacco control policies: the International Tobacco Control Policy Evaluation Project (the ITC Project): Table 1

2006· review· en· W1970620442 on OpenAlexafffund
Geoffrey T. Fong, K. Michael Cummings, Donald R. Shopland

Bibliographic record

VenueTobacco Control · 2006
Typereview
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Waterloo
FundersNational Cancer InstituteCanadian Institutes of Health Research
KeywordsTobacco controlConventionTobacco industryConceptual frameworkPolitical sciencePopulationPublic relationsEnvironmental healthPublic healthMedicineSociologySocial scienceLaw

Abstract

fetched live from OpenAlex

The Framework Convention on Tobacco Control (FCTC) is a seminal event in tobacco control and in global health. Scientific evidence guided the creation of the FCTC, and as the treaty moves into its implementation phase, scientific evidence can be used to guide the formulation of evidence-based tobacco control policies. The International Tobacco Control Policy Evaluation Project (ITC Project) is a transdisciplinary international collaboration of tobacco control researchers who have created research studies to evaluate and understand the psychosocial and behavioural impact of FCTC policies as they are implemented in participating ITC countries, which together are inhabited by over 45% of the world's smokers. This introduction to the ITC Project supplement of Tobacco Control presents a brief outline of the ITC Project, including a summary of key findings to date. The overall conceptual model and methodology of the ITC Project--involving representative national cohort surveys created from a common conceptual model, with common methods and measures across countries--may hold promise as a useful paradigm in efforts to evaluate and understand the impact of population-based interventions in other important domains of health, such as obesity.

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)0.008
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
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 head0.088
GPT teacher head0.429
Teacher spread0.341 · 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 designOther design
Domainnot available
GenreReview

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

Citations46
Published2006
Admission routes2
Has abstractyes

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