A Taxing Dilemma: Assessing the Impact of Tax and Price Changes on the Tobacco Market
Bibliographic record
Abstract
Sales of contraband cigarettes in Canada constitute a sizable component of the tobacco market. This illegal trade is associated with a loss in tax revenue and an array of illicit activities that involve gangs and organized crime. Various policy responses have been called for to counter this state of affairs. Increased policing and controls have resulted in the market share of the illegal product declining significantly to about 20 percent in 2010 from about one-third two years earlier. In addition to allocating more resources in order to control the problem, governments have been urged to lower tobacco taxes in the belief that lower relative prices for the legal product will induce smokers to switch in significant numbers away from the illegal supply source, perhaps also increasing tax revenues. This report analyzes the impact of tax and price changes on the composition of the cigarette market in the context of a demand-driven analytical model, in which smokers shift between legal and illegal products to a significant degree.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".