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Record W2055245941 · doi:10.4269/ajtmh.15-0154

Stopping Murder by Medicine: Introducing the Model Law on Medicine Crime

2015· article· en· W2055245941 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Tropical Medicine and Hygiene · 2015
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLicenseLaw enforcementLawCriminal lawEnforcementBusinessIncentivePolitical scienceEconomics

Abstract

fetched live from OpenAlex

The iatrogenic pandemic of untreated illness related to falsified and substandard medicines is intolerable, but has a logical explanation: in many countries, inadequate laws make it barely illegal to manufacture or distribute poor-quality medicines. The law hardly punishes those who intentionally or recklessly deal in falsified or substandard medicine, when clearly it should criminalize these perpetrators in proportion to the grievous--even fatal--injury they inflict on public health. To solve this omission, this article presents a new Model Law on Medicine Crime, which countries may freely use as a template for strengthening their national laws. The Model Law includes criminal prohibitions against manufacturing, trafficking, or selling poor-quality medicines; principles for appropriately punishing offenders; special provisions for Internet-based medicine crimes; tools for encouraging whistle-blowers to cooperate with law enforcement; incentives for developing governments to strengthen their drug regulatory capacity; and important exceptions to prevent the law being abused, such as to prevent the prosecution of legitimate medical researchers or to prevent good-quality generic medicines being seized while in transit. The Model Law is discussed and explained and is offered free of charge under a Creative Commons license to any governments wanting to implement it.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.093
GPT teacher head0.388
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it