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Record W7005147829

THE POWER OF PILLS: SOCIAL, ETHICAL AND LEGAL ISSUES IN DRUG DEVELOPMENT, MARKETING, AND PRICING

2006· other· en· W7005147829 on OpenAlexaboutno aff

Bibliographic record

VenueDigitalGeorgetown (Georgetown University Library) · 2006
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsnot available
Fundersnot available
KeywordsPharmaceutical industryDrug pricingDutyPower (physics)PoliticsEconomic JusticeDrug industryProfit (economics)Public health
DOInot available

Abstract

fetched live from OpenAlex

List of abbreviation -- Introduction -- Pt. I. Pharmaceutical industry profits and obligations -- 1. The pharmaceutical industry and the pursuit of profit / Joel Lexchin -- 2. Social, ethical, and legal issues in drug development, marketing, and pricing policies: setting priorities: pharmaceuticals as private organizations and the duty to make money/maximize profits / Kristina M. Lybecker -- 3. The pharmaceutical industry and its obligations in the developing world / Ann Mills, Patricia Werhane, and Michael Gorman -- 4. Drug companies as organizational hybrids / Warren Kaplan -- 5. Physicians and the pharmaceutical industry: a symbiotic relationship? / Ian E. Marshall -- 6. Industry perspectives on equity, access, and corporate social responsibility: a view from the inside / Robert A. Freeman -- Pt. II. Justice medicines as global public goods -- 7. Pharmaceuticals, public health, and the law: a public health perspective / Wendy E. Parmet -- 8. Access to medications and global justice / David B. Resnik -- 9. Pharmacogenetics and global (in)justice / Søren Holm -- Pt. III. The social, ethical, and political challenge: neglected diseases -- 10. The enduring crisis in neglected diseases / Nathan Ford -- 11. Moving beyond charity for R&D for neglected diseases / James Orbinski and Barry Burciul -- 12. Neglected disease research: health needs and new models for R&D / Aidan Hollis -- 13. Advanced purchase commitments: moral and practical problems / Donald W. Light -- 14. Harnessing the power of pharmaceutical innovation / Thomas Pogge -- Pt. IV. Patents and access to medicines -- 15. Patents, profits, and the price of pills: implications for access and availability / Michael J. Selgelid and Eline M. Sepers -- 16. Fair followers: expanding access to generic pharmaceuticals for low- and middle-income populations / Kevin Outterson -- 17. Abolishing the product patent: a step forward for global access to drugs / Adam Mannan and Alan Story -- 18. Trading health for profit: the impact of bilateral and regional free trade agreements on domestic intellectual property rules on pharmaceuticals / Lisa Forman -- Pt. V. Research ethics -- 19. Human genomic research ethics: changing the rules / Steven H. Miles -- 20. Assumptions in the "standard of care" debate / Florencia Luna -- Pt. VI. Political activism and treatment access -- 21. Medicines for all? Commitment and compromise in the fight for Canada's law on compulsory licensing for export / Richard Elliot -- 22. Placing access to essential medicines on the human rights agenda / Brook K. Baker -- Pt. VII. National responsibilities -- 23. Producing affordable medicines in South Africa / João L. Carapinha -- 24. National responsibility in the provision of basic medicines / Kinsley Wilson, Laura Esmail, and Jillian Clare Cohen -- 25. Pharmaceutical cost-effectiveness pricing: developing and protecting a global ideal form / Thomas A. Faunce -- Notes on the contributors -- Index

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.069
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0030.005
Scholarly communication0.0070.007
Open science0.0010.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0690.023

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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2006
Admission routes1
Has abstractyes

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