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Record W7075628612

REPROGENETICS: LAW, POLICY, AND ETHICAL ISSUES

2007· other· en· W7075628612 on OpenAlexaboutno aff

Bibliographic record

VenueDigitalGeorgetown (Georgetown University Library) · 2007
Typeother
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsEugenicsEthical issuesPublic policyCorporate governanceKingdomPoliticsWhite (mutation)Public consultationWhite paper
DOInot available

Abstract

fetched live from OpenAlex

List of contributors -- Preface -- Pt. I. The historical and regulatory landscape -- Ch. 1. On drawing lessons from the history of eugenics / Diane B. Paul -- Ch. 2. Governmental regulation of genetic technology, and the lessons learned / Julie Gage Palmer -- Ch. 3. Oversight of assisted reproductive technologies: the last twenty years / Andrea L. Bonnicksen -- Pt. II. Ethical issues in reprogenetics -- Ch. 4. Market transactions in reprogenetics: a case for regulation / Suzanne Holland -- Ch. 5. Stem cells, clones, consensus, and the law / Timothy Caulfield -- Pt. III. International regulation of reprogenetics -- Ch. 6. The governance of reprogenetic technology: international models / Lori P. Knowles -- Ch. 7. Regulating reprogenetics in the United Kingdom / Andrew Grubb -- Ch. 8. The evolution of public policy on reprogenetics in Canada / Patricia A. Baird -- Pt. IV. Regulating reprogenetics in the United States / Ch. 9. A brief history of public debate about reproductive technologies: politics and commissions / Kathi E. Hanna -- Ch. 10. Possible policy strategies for the United States: comparative lessons / Alison Harvison Young -- Ch. 11. The development of reprogenetic policy and practice in the United States: looking to the United Kingdom / Gladys B. White -- Ch. 12. Reprogenetics and public policy: reflections and recommendations / Erik Parns and Lori P. Knowles -- 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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.499
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0020.001
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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2007
Admission routes1
Has abstractyes

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