MétaCan
Menu
Back to cohort
Record W2792299162 · doi:10.18332/tid/84159

Member states of the FCTC can generate self-sustaining funding by applying the polluter-pay principle to the tobacco industry

2018· article· en· W2792299162 on OpenAlexaff
Neil Collishaw, Cynthia Callard

Bibliographic record

VenueTobacco Induced Diseases · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEU Law and Policy Analysis
Canadian institutionsPhysicians for a Smoke-Free Canada
Fundersnot available
KeywordsPolluter pays principleBusinessMember statesTobacco industryLaw and economicsEnvironmental healthLawEuropean unionEconomicsPolitical scienceMedicineInternational trade

Abstract

fetched live from OpenAlex

Background and challenges to implementation Compared to the size of the problem and the public health work to be done, the FCTC remains woefully underfunded. Past attempts to raise funds, whether through assessed contributions, voluntary contributions, Overseas Development Assistance or other means have not generated funds commensurate with the size of the problem. Intervention or response The FCTC contains mechanisms for establishing subisidiary bodies. One such body could be established to receive funds from a new levy on tobacco revenue. For most FCTC member states this levy would be on money about to leave the country, destined for the head offices of multinational tobacco companies. Member states could agree to send a portion of the money so raised to WHO for global tobacco control programming. The rest could be used for national and regional tobacco control work. Results and lessons learnt A 5% levy, administered globally, would yield about USD one billion per year. If USD 200 million were designated for global tobacco control, Member States would collectively still have USD 800 million to spend on national and regional tobacco control programming. Conclusions and key recommendations At the next meeting of the Conference of the Parties, FCTC Member States should agree on a new globally coordinated tobacco levy, to be imposed by each Member State. At least USD 200 million should be designated for global tobacco control programming, to be administered by WHO, with the remainder of the proceeds from the levy to be spent on national and regional tobacco control programming.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.343
Teacher spread0.303 · 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 designNot applicable
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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueTobacco Induced DiseasesSame topicEU Law and Policy AnalysisFrench-language works237,207