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
Drs. Lee and Chen provide data on the effects of price and smoking characteristics and their relationship to smuggled cigarettes in Taiwan.Smuggled cigarette smoking increased for each NT$1 increase in the price of legal cigarettes.Globally, cigarette smuggling as a percent of consumption varies widely.In Israel, it is estimated that 44% of the cigarettes are smuggled (1999 WHO).In Hungary, the rate is 9% and in Egypt it is slightly above 1%.Researchers estimate that 30% of the internationally exported cigarettes (about 355 billion cigarettes) are lost to smuggling.This trend is seen globally, both in the developed and developing world.Cigarette taxes are often used to plug holes in budgets at all levels of government.Here in my home state of New Jersey, for instance, the newly proposed tax for July 2006 on a pack of cigarettes is $2.75, up from the current $2.40 USD per pack.Initially, state and federal governments benefited from the increased revenue, and we saw the desired decrease in cigarette consumption.But over time, sales of legal cigarettes decreased and illegal cigarettes were smuggled into the higher tax states for resale.A report from Tobacco Free Kids estimates that approximately one-quarter of all legally exported cigarettes end up smuggled across international borders.The World Bank ( Joossens, 1999; De Beyer, 2002) has identified countries with high and low smuggling rates.Sweden, Denmark, Norway, France, Finland, and Ireland-all with high cigarette prices and taxes-are reported to have low smuggling rates (,5%).Countries with low cigarette prices and taxes are reported to have higher smuggling rates (.10%): Spain, Italy, Pakistan, Nigeria, Yugoslavia, Ukraine, Moldova, Columbia, Iran, Austria, and Cambodia.Similar to the recommendations made by other researchers, the authors sanction better controls, forgery-proof tobacco tax stamps, and other regulatory systems.The task will be difficult given that we estimate overall smoking prevalence is still about 29% globally, with more than 82% of smokers belonging to low- and middle-income groups.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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