Internet Cigarette Vendor Compliance With Credit Card Payment and Shipping Bans
Bibliographic record
Abstract
INTRODUCTION: Most Internet cigarette sales have violated taxation and youth access laws, leading to landmark 2005 agreements with credit card companies, PayPal, and private shippers (United Parcel Service, Federal Express, DHL) to cease participation in these transactions. Despite their promise at the time, loopholes allowed for check payment and U.S. Postal Service (USPS) shipping. This study assessed actual vendor compliance with the payment and shipping bans using a purchase survey. METHODS: In late 2007 and early 2008, an adult buyer attempted to order cigarettes from the 97 most popular Internet cigarette vendors (ICVs) using banned payment and shipping methods. When banned payment or shipping methods were unavailable, purchases were attempted with alternate methods (e.g., checks, e-checks, USPS). RESULTS: Twenty-seven of 100 orders were placed with (banned) credit cards; 23 were successfully received. Seventy-one orders were placed with checks (60 successfully received). Four orders were delivered using banned shippers; 79 of 83 successfully received orders were delivered by the USPS. CONCLUSIONS: About a quarter of ICVs violated the payment ban, others adapted by accepting checks. Most vendors complied with the shipping ban, perhaps because USPS was an easy substitute shipping option. Better enforcement of the bans is needed; the 2009 Prevent All Cigarette Trafficking Act closed the USPS loophole by making cigarettes nonmailable material; evaluation of enforcement efforts and adaptations by vendors are needed. These sorts of bans are a promising approach to controlling the sale of restricted goods online.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".