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Record W2129728571 · doi:10.1558/hrge.v17i1.7

Courts, Legislators and Human Embryo Research: Lessons from Ireland

2011· article· en· W2129728571 on OpenAlexaff
William Binchy

Bibliographic record

VenueHuman Reproduction & Genetic Ethics · 2011
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsTrinity College
Fundersnot available
KeywordsNormativeSanctionsLawHuman rightsSociologyPolitical scienceLegislationPosition (finance)IrishLaw and economics

Abstract

fetched live from OpenAlex

When it comes to the matter of human embryo research law plays a crucial role in its development by helping to set the boundaries of what may be done, the sanctions for acting outside those boundaries and the rights and responsibilities of key parties. Nevertheless, the philosophical challenges raised by human embryo research, even with the best will of all concerned, may prove too great for satisfactory resolution through the legal process. Taking as its focus the position of Ireland, this paper explores the distinctive constitutional approach taken on this issue and addresses the difficulty of translating sound philosophy into judicial decrees and the difficulty of establishing expert commissions to make law reform proposals on matters of profound normative controversy. It concludes that the Irish experience does have useful lessons for those in other countries who are concerned with the legal approach to research on human embryos and points to the desirability of a diversity of normative positions in order to enrich the quality of the analysis so as to encourage more informed debate in society.

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)0.024
metaresearch head score (Gemma)0.033
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: none
Teacher disagreement score0.187
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.033
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0080.031
Scholarly communication0.0160.008
Open science0.0020.008
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.391
GPT teacher head0.450
Teacher spread0.059 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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