MétaCan
Menu
Back to cohort
Record W2906206060 · doi:10.3968/10512

Legal and Economic Analysis of Medicine Purchased Oversea

2018· article· en· W2906206060 on OpenAlexvenueno aff
Bo Feng

Bibliographic record

VenueCanadian social science · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPrinciple of legalityIntellectual propertyCounterfeitBusinessPurchasingBalance (ability)Law and economicsLawMedicineMarketingEconomicsPolitical science

Abstract

fetched live from OpenAlex

In recent years, the phenomenon of purchasing medicine abroad has gradually increased. In particular, it has resulted in major cases with great social influence, such as the case of “Lu Yong Selling Counterfeit Medicine”. It has sparked an intense debate on the legality of oversea purchase of medicine. Although the treatment expense is greatly reduced for the patients, oversea purchase of medicine is suspected to undermine intellectual property protection. Finding a balance between “inspiring pharmaceutical companies to innovate” and “making it affordable to patients” is the key to solve the problem of oversea purchase of medicine. Based on the analysis of the positive and negative effects of overseas purchase of medicine, this paper proposes the principle of “consideration of protection and antitrust”, which not only protects the intellectual property rights of the medicine, but also prevents companies from abusing intellectual property rights.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0130.000

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 head0.046
GPT teacher head0.306
Teacher spread0.260 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCanadian social scienceSame topicPharmaceutical Economics and PolicyFrench-language works237,207