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Record W1524370281 · doi:10.1093/pch/11.10.655

Medical emergencies in children of orthodox Jehovah's Witness families: Three recent legal cases, ethical issues and proposals for management

2006· article· en· W1524370281 on OpenAlexaffabout
Juliet Guichon, Ian Mitchell

Bibliographic record

VenuePaediatrics & Child Health · 2006
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWitnessCompetence (human resources)Coercion (linguistics)Statutory lawMedicineParental consentPsychologyInformed consentLawPolitical scienceSocial psychologyAlternative medicine

Abstract

fetched live from OpenAlex

Three recent Canadian legal cases have dealt with the proposed blood transfusion of adolescent members of Jehovah's Witness (JW) families. In each case, the court permitted transfusions if medically necessary. Much critical analysis of the issue of forced treatment of decisionally competent adolescents focuses exclusively on competence and questions why mature minors may not decide for themselves. The authors argue that a focus on decision-making competence alone is too narrow. Before one may legally give or refuse consent to medical treatment, three conditions must be met: competence, adequate information and lack of coercion. In striving to find agreement on medical treatment, physicians, patients and JW family members seek and, in fact, often achieve mutual understanding and cooperation. Coercion by actual or threatened shunning and excommunication can occur, and these factors may affect adolescent decision-making. In this context, a court order authorizing medical treatment can, therefore, be seen as enhancing patient freedom. The authors suggest that, in addition to fulfilling existing statutory duties to report a child in need of protection, health care professionals caring for acute patients of JW families should actively look for evidence that the patient has accurate medical information and is acting without coercion. The authors also explore suggestions on how to deal with the unusual complexities of such cases.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.005
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.362
Teacher spread0.335 · 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 designCase report
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

Citations19
Published2006
Admission routes2
Has abstractyes

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