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Record W3044386406

Rethinking Canadian Legal Approaches to Frozen Embryo Disputes

2014· article· en· W3044386406 on OpenAlexfundaboutno aff
Stefanie Carsley

Bibliographic record

VenueeYLS (Yale Law School) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsPolitical scienceLawSociologyLaw and economics
DOInot available

Abstract

fetched live from OpenAlex

This article examines and critiques Canadian legal responses to disputes over frozen in vitro embryos. It argues that current laws that provide spouses or partners with joint control over the use and disposition of embryos created from their genetic materials and that mandate the creation of agreements setting out these parties' intentions in the event of a disagreement or divorce overlook the experiences of women who undergo in vitro fertilization treatment. It also maintains that these laws do not accord with how Canadian law and public policy has responded to similar conflicts between spouses, or to agreements that seek to control or restrict women's reproductive choices. This article considers how legislatures and courts in other jurisdictions have sought to respond to embryo disposition disputes, but argues that their respective approaches raise similar issues and would pose additional problems within the Canadian context. It ultimately provides recommendations for how Canadian laws might better support the express objectives of the Assisted Human Reproduction Act and Quebec's Act Respecting Clinical and Research Activities Relating to Assisted Procreation to protect the health and well-being of women, to promote the principle of free and informed consent and to recognize that women are more directly affected than men by the use of assisted reproductive technologies.

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)0.027
metaresearch head score (Gemma)0.049
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: Empirical · Consensus signal: none
Teacher disagreement score0.272
Threshold uncertainty score0.844

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.009
Science and technology studies0.0550.055
Scholarly communication0.0230.008
Open science0.0100.010
Research integrity0.0150.016
Insufficient payload (model declined to judge)0.0070.000

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 head0.055
GPT teacher head0.261
Teacher spread0.206 · 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
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

Citations0
Published2014
Admission routes2
Has abstractyes

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