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Record W2926153805

Natural Incubators: Somatic Support as Reproductive Technology, and the Comparative Constitutional Implications on Cases of Maternal Brain Death in the U.S., Canada, and Ireland

2016· article· en· W2926153805 on OpenAlexaboutno aff
Sonya Laddon Rahders

Bibliographic record

VenueHastings women's law journal · 2016
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsSomatic cellNatural (archaeology)Political scienceDemographyHistorySociologyBiologyArchaeologyGenetics
DOInot available

Abstract

fetched live from OpenAlex

Should a brain dead pregnant person be kept alive on life support, despite the family's wishes otherwise, in order to fully gestate the fetus? A 2013 grand rounds study out of United Arab Emirates found that medical technology has reached such an advanced stage that gestational age is no longer a barrier to whether or not a pregnant person may be kept on somatic support until the fetus is delivered. The study concluded that a brain dead pregnant person might serve as a "natural incubator" and successfully deliver a baby after the mother becomes brain dead at just 16 weeks' gestation. This comment examines maternal brain death from the lenses of both reproductive technologies and constitutional rights. If medical providers believe that the technology exists to make a dead body a beneficial "natural incubator," regardless of gestational age of the fetus or the family's wishes, the author warns that we risk losing the ability to draw the line between active reproduction and passive incubation in the female body. The author also draws upon comparisons between the U.S., Canada, and Ireland, and contributes to the legal dialogue about what rights an individual has against the state in cases of maternal brain death, and what the implications may be for assisted reproductive technologies and reproductive rights in the future.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.294
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2016
Admission routes1
Has abstractyes

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