Hungry for tobacco: an analysis of the economic impact of tobacco consumption on the poor in Bangladesh
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To investigate the extent of tobacco expenditures in Bangladesh and to compare those costs with potential investment in food and other essential items. DESIGN: Review of available statistics and calculations based thereon. RESULTS: Expenditure on tobacco, particularly cigarettes, represents a major burden for impoverished Bangladeshis. The poorest (household income of less than $24/month) are twice as likely to smoke as the wealthiest (household income of more than $118/month). Average male cigarette smokers spend more than twice as much on cigarettes as per capita expenditure on clothing, housing, health and education combined. The typical poor smoker could easily add over 500 calories to the diet of one or two children with his or her daily tobacco expenditure. An estimated 10.5 million people currently malnourished could have an adequate diet if money on tobacco were spent on food instead. The lives of 350 children could be saved each day. CONCLUSION: Tobacco expenditures exacerbate the effects of poverty and cause significant deterioration in living standards among the poor. This aspect of tobacco use has been largely neglected by those working in poverty and tobacco control. Strong tobacco control measures could have immediate impact on the health of the poor by decreasing tobacco expenditures and thus significantly increasing the resources of the poor. Addressing the issue of tobacco and poverty together could make tobacco control a higher priority for poor countries.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it