Deadly Discounts: How Reimportation Jeopardizes the Safety of the U.S. Pharmaceutical Drug Supply under the Federal Trade Commission Amendment
Bibliographic record
Abstract
The amendment to a Federal Trade Commission (FTC) reauthorization bill, previously introduced as Senate Bill 334 (S.334) Pharmaceutical Market Access and Drug Safety Act of 2005 allows for the reimportation of prescription drugs into the United States from approximately 25 countries, including Canada via Internet pharmacies. There are no guarantees that the internet websites advertising as Canadian pharmacies are legitimate. The shipping of pharmaceutical drugs occurs through importation, which refers to drugs produced abroad then later shipped to the U.S., or re-importation, a term applied when drugs are produced in the U.S. and exported for sale to foreign countries and later imported back into the U.S.\nThe amendment attempts to open the border doors even further by allowing increased importation of medicine and requires pharmacies and drug wholesalers to register with the FDA. The potential importers will be subject to frequent, random inspection; however, these inspections are inadequate and more must be done. Some real solutions include electronic pedigrees and authentication technologies. Also, technology must be rotated so that illegitimate manufacturers can not adapt and overcome anti-counterfeiting measures.
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 | 0.015 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 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".