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Record W2152992596 · doi:10.1136/tc.2010.039735

Tobacco and poverty: evidence from Vietnam

2011· review· en· W2152992596 on OpenAlexaff
Debra Efroymson, Hoang Anh Pham, Lori Jones, Sian Fitzgerald, Le Thi Thu, Lê Thị Thu Hiền

Bibliographic record

VenueTobacco Control · 2011
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsPierre Elliott Trudeau Foundation
FundersInternational Union Against Tuberculosis and Lung Disease
KeywordsRibonucleotide reductaseCisplatinDNA repairERCC1DNA damageNucleotide excision repairHomologous recombinationCell cycleDNA replicationGene knockdownRAD51Molecular biologyChemistrySister chromatidsBiologyProtein subunitDNACellBiochemistryGeneticsApoptosisGene

Abstract

fetched live from OpenAlex

This review examined existing evidence to investigate the link between tobacco and poverty in Vietnam, to assess the impact of tobacco control policies on employment related to tobacco consumption and to identify information gaps that require further research for the purposes of advocating stronger tobacco control policies. A Medline, PubMed and Google Scholar search identified studies addressing the tobacco and poverty association in Vietnam using extensive criteria. In all, 22 articles related either to tobacco and health or economics, or to the potential impact of tobacco control policies, were identified from titles, abstracts or the full text. 28 additional publications were identified by other means. PHA, LTT and LTTH reviewed the publications and prepared the initial literature review. There is extensive evidence that tobacco use contributes to poverty and inequality in Vietnam and that tobacco control policies would not have a negative impact on overall employment. Tobacco use wastes household and national financial resources and widens social inequality. The implementation and enforcement of a range of tobacco control measures could prove beneficial not only to improve public health but also to alleviate poverty.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.075
GPT teacher head0.339
Teacher spread0.264 · 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; both teacher heads agree on what is shown here.

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

Citations19
Published2011
Admission routes1
Has abstractyes

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