Populations and genetics : legal and socio-ethical perspectives
Bibliographic record
Abstract
Acknowledgements -- In memoriam -- Prologue / Bartha Maria Knoppers -- Sect. 1. Of biobanks and databases -- UK DNA sample collections for research / Frances C. Rawle -- Estonian genome project: large scale health status description and DNA collection / Andres Rannamae -- Surveying the population biobankers / Genevieve Cardinal, Mylene Deschenes -- The Israeli DNA and cell line collection: a human diversity repository / David Gurwitz, Orit Kimchi, Batsheva Bonne-Tamir -- DNA Data Bank of Japan as an indispensable public database / Satoru Miyazaki and Yoshio Tateno - - A survey of the variability of DNA banks worldwide / Nicole Palmour -- An empirical survey on biobanking of human genetic material and data in six EU countries / Anne Cambon-Thomsen, I. Hirtzlin, N. Preaubert, C. Dubreuil, J. Duchier, B. Jansen, J. Simon, P. Lobato de Faria, A. Perez-Lezaun, B. Visser, G. Williams, J.C. Galloux and on behalf of the Eurogenbank Consortium -- Mutation databases and ethical considerations / Richard G.H. Colton, Ourania Horaitis -- Sect. 2. Of populations and communities -- Community engagement in genetic research: the "slow code" of research ethics? / Eric T. Juengst -- Competing perspectives on reasons for participation and non-participation in the North Cumbria Community genetics project / Erica Haimes, Michael Whong- Barr -- The engagement of consumers in genetics education: lessons learned / Michele A. Lloyd-Puryear, Penny Kyler, Gloria Weissman - - Racial profiling of DNA samples: will it affect scientific knowledge about human genetic variation? / Sandra Soo-Jin Lee and Barbara A. Koenig -- Problematizing the notion of "community" in research ethics / Fern Brunger -- On the intersection of privacy, consent, commerce and genetics research / Jon F. Merz -- A Presumed-consent model for regulating informed consent of genetic research involving DNA banking / Bernice Elger, Alexandre Mauron - - Ethical and legal issues in genetic biobanking / John A. Robertson -- Do the ethical duties of donor, and administrators, depend on whether the database is public or private? / Darryl Macer -- Public attitudes to participating in UK biobank : a DNA bank, lifestyle and morbidity database on 500,000 members of the UK public aged 45-69 / Darren Shickle, Rhydian Hapgood, Jane Carlisle, Phil Shackley; Ann Morgan and Chris McCabe -- Sect. 3. Of commerce, patents and benefit-sharing commercial biobanks and genetic research: banking without checks? / Mary Ruth Anderlik -- PXE International: harnessing intellectual property law for benefit- sharing / Patrick F. Terry -- Advances in science and progress of humanity: a global perspective on DNA sampling / Huanming Yang - - Benefit-sharing in the new genomic marketplace: expanding the ethical frame of reference / Ted Schrecker -- Harmonizing commercialisation and gene patent policy with other social goals / Lorraine Sheremeta, E. Richard Gold, and Timothy Caulfield -- Preliminary data on U.S. DNA based patents and plans for a survey of licensing practices / Robert Cook-Deegan; LeRoy Walters, Lori Pressman, Derrick Pau, Stephen McCormack, Janella Gatchauan, and Richard Burges -- Towards a universal definition of "benefit- sharing" / Maria Graciela De Ortuzar -- Do patents encourage or inhibit genomics as a global public good? / Halla Thorsteindottir, Abdallah S. Daar, Richard D. Smith, Peter A. Singer -- Patents and benefit-sharing as a challenge for corporate ethics / Chris Macdonald -- Pharmaceutical patents and benefit-sharing: evolution of drug accessibility in Brazil since the 1980's / M.B. Marques - - Reconciling social justice and economic opportunism: regulating the Newfoundland genome / Daryl Pullman, Andrew Latus -- Sect. 4. Of information and discrimination -- Attitudes to genetic research and uses of genetic information: support, concerns and genetic discrimination / Martin Richards -- Genetic information and insurance: some issues / Charles Black -- Discrimination / Moussa Charafeddine -- "Genetic discrimination" in an international context / Dorothy C. Wertz -- Additional ethical issues in genetic medicine perceived by the potential patients / Jackie Leach Scully, Christine Rippberger, Christoph Rehmann-Sutter -- Epilogue- statement of principles on the ethical conduct of human genetic research involving populations -- Why another statement from the RMGA? / Claude Laberge
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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 | 0.078 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.117 |
| Scholarly communication | 0.021 | 0.019 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.023 | 0.028 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".