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Record W2520683306 · doi:10.1111/apa.13590

Focusing on relationships, not information, respects autonomy during antenatal consultations

2016· article· en· W2520683306 on OpenAlexaff
Nathalie Gaucher, Antoine Payot

Bibliographic record

VenueActa Paediatrica · 2016
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsAutonomyInterdependenceMedicineDoctrineInformed consentNursingPublic relationsAlternative medicineLawPolitical science

Abstract

fetched live from OpenAlex

Policy statements regarding antenatal consultations for preterm labour are guided by physicians' concerns for upholding the legal doctrine of informed consent, through the provision of standardised homogeneous medical information. This approach, led by classical in-control conceptions of patient autonomy, conceives moral agents as rational, independent, self-sufficient decision-makers. Recent studies on these antenatal consultations have explored patients' perspectives, and these differ from guidelines' suggestions. Relational autonomy - which understands moral agents as rational, emotional, creative and interdependent - resonates impressively with these new data. CONCLUSION: A model for antenatal consultations is proposed. This approach encourages clinicians to explore individual patients' lived experiences and engage in trusting empowering relationships. Moreover, it calls on physicians to enhance patients' relational autonomy by becoming advocates for their patients within healthcare institutions and professional organisations, while calling for broadscale policy changes to encourage further funding and support in investigations of the patient's voice.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.029
GPT teacher head0.287
Teacher spread0.259 · 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

Citations30
Published2016
Admission routes1
Has abstractyes

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