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Record W4383426465 · doi:10.7202/1101134ar

Recent Canadian Negligence Decisions Relating to Prenatal Care: Implications for Physicians’ Screening Practices

2023· article· en· W4383426465 on OpenAlexafffundvenueabout
Blake Murdoch

Bibliographic record

VenueCanadian Journal of Bioethics · 2023
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsUniversity of Alberta
FundersGenome AlbertaGenome Canada
KeywordsPlaintiffHarmLiabilityCausationAutonomyMalpracticeMedicineTortHealth carePsychologyMedical emergencyFamily medicineLawPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

This article summarizes several Canadian court decisions from 2015 onward stemming from wrongful birth and wrongful life litigation. Plaintiff success often turns on whether causation is established, on a balance of probabilities, between a physician’s breach of standard of care and the harm to the parents and/or the child later born. Physicians’ failure to offer or order screening or diagnostic tests has been a source of wrongful birth liability, as too can be failure to ensure patient understanding of results. Physicians should ensure that they recommend diagnostic testing when presented with concerning clinical indications in accordance with professional practice guidance. Given non-invasive prenatal screening’s (NIPS) advantages and the threat of wrongful birth liability for failure to discuss this procedure, it is likely to be propelled into an ever more prominent position as a first-choice offering for aneuploidy screening. Appropriately cautious physician behaviour involves discussing and offering NIPS, and also involves ensuring that results are understood. This can reduce physician liability, improve patient reproductive autonomy, and sometimes benefit patient health by preventing or lessening trauma that informed women may opt to mitigate when granted the opportunity.

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)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.187
GPT teacher head0.406
Teacher spread0.219 · 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 designOther design
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
Published2023
Admission routes4
Has abstractyes

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