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Record W2614824727

Banning Bans on New Reproductive and Novel Genetic Technologies

2003· article· en· W2614824727 on OpenAlexaboutno aff
Matthew Herder

Bibliographic record

VenueeYLS (Yale Law School) · 2003
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsReproductive technologyBusinessInternet privacyLawBiologyComputer sciencePolitical scienceGeneticsPregnancy
DOInot available

Abstract

fetched live from OpenAlex

Commentators argue that statutory prohibitions with the force of the criminal law should not be used to regulate new reproductive technologies (NRTs) and novel genetic technologies (NGTs). Bill C-13, the Assisted Human Reproduction Act, however, codifies 10 criminal bans. This paper considers the merits of the various arguments levied against Bill C-13, and the corollary claim that only a "non-prohibitive" model of legislation befits NRTs and NGTs. Three types of arguments are used to critique criminal bans: (1) "Structural" arguments hinge on the constraints of the Canadian legal system - legislation complete with prohibitions runs afoul of the Constitution Act 1867, violates the Canadian Charter of Rights and Freedoms, and cannot keep pace with scientific progress. (2) "Consequentialist" arguments focus on the potential results of enacting a statute carrying criminal bans - criminalization will chill research, drive research underground, encourage researcher forum shopping, fuel public misperception by reinforcing genetic determinism, and effectively foreclose important dialogue on NRTs and NGTs. (3) "Theoretical" arguments relate to the very nature of criminal law - prohibitions will be unenforceable; the criminal law, a model of "command and control", will be ineffective in shaping research practice; and moral ambiguity can support only regulation, as consensus is a sine qua none for criminal bans. All the arguments in opposition to criminal bans prove unpersuasive; moreover, they fail to substantiate a non-prohibitive alternative for NRT-NGT regulation. Bill C-13 should therefore be proclaimed into law; perhaps then commentators will actually theorize about the harms, or lack thereof, of particular NRTs and NGTs.

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)0.022
metaresearch head score (Gemma)0.032
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: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.574
Threshold uncertainty score0.858

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0100.039
Scholarly communication0.0080.006
Open science0.0050.005
Research integrity0.0190.016
Insufficient payload (model declined to judge)0.0100.002

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.

Opus teacher head0.029
GPT teacher head0.284
Teacher spread0.256 · 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
GenreCommentary

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
Published2003
Admission routes1
Has abstractyes

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