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Obstetrical Delivery of the HIV-Positive Woman: Legal and Ethical Considerations

2001· review· en· W2328345446 on OpenAlexaff
Susan E. Scarrow

Bibliographic record

VenueObstetrical & Gynecological Survey · 2001
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsMedicineAutonomyContext (archaeology)Psychological interventionInformed consentHuman immunodeficiency virus (HIV)Personal autonomyEthical issuesFamily medicineNursingAlternative medicineEngineering ethicsLawPathology

Abstract

fetched live from OpenAlex

Every year, thousands of perinatally HIV-infected children are born, resulting in debate about appropriate HIV treatment and interventions for pregnant women. Recent medical studies endorse the use of the cesarean delivery to reduce vertical (mother to infant) transmission of HIV. In addition to medical questions, this practice raises legal and ethical considerations for the attending physician. In the context of AIDS prevention, the potential exists for reasoned and well-informed decision making to give way to encouragement, and even duress, in cases where a woman refuses recommended surgical delivery. However, in such cases, the role of the physician should remain as that of an informed educator and counselor, enabling the patient to exercise her autonomy and personal choice within her social and cultural context. Target Audience: Obstetricians & Gynecologists, Family Physicians Learning Objectives: After completion of this article, the reader will be able to explain the legal and ethical dimensions of informed consent, to describe how informed consent can be applied to the clinical counseling of HIV-infected pregnant women, and to outline the physician guidelines for decision making when counseling an HIV-infected pregnant patient.

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)0.084
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.842
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.084
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.101
GPT teacher head0.380
Teacher spread0.279 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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
Published2001
Admission routes1
Has abstractyes

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