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Record W2033350049 · doi:10.3386/w15468

Investments in Pharmaceuticals Before and After TRIPS

2009· report· en· W2033350049 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

VenueNational Bureau of Economic Research · 2009
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTRIPS architectureBusinessChemistryTransport engineeringEngineering

Abstract

fetched live from OpenAlex

We examine the relationship between patent protection for pharmaceuticals and investment in development of new drugs. Patent protection has increased around the world as a consequence of the TRIPS Agreement, which specifies minimum levels of intellectual property protection for members of the World Trade Organization. It is generally argued that patents are critical for pharmaceutical research efforts, and so greater patent protection in developing and least-developed countries might result in greater effort by pharmaceutical firms to develop drugs that are especially needed in those countries. Since patents also have the potential to reduce access to treatments through higher prices, it is imperative to assess whether the benefits of increased incentives have materialized in research on diseases that particularly affect the poor. We find that patent protection is associated with increases in research and development (R&D) effort when adopted in high income countries. However, the introduction of patents in developing countries has not been followed by greater investment. Particularly for diseases that primarily affect the poorest countries, our results suggest that alternative mechanisms for inducing R&D may be more appropriate than patents.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.600
GPT teacher head0.490
Teacher spread0.110 · 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