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Record W2803121690 · doi:10.1093/pch/pxy047

Children need privacy too: Respecting confidentiality in paediatric practice

2018· article· en· W2803121690 on OpenAlexafffund
Justine Noiseux, Harold Rich, Nathalie Bouchard, Crystal Noronha, Franco A. Carnevale

Bibliographic record

VenuePaediatrics & Child Health · 2018
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsDouglas Mental Health University InstituteMcGill UniversityMontreal Children's Hospital
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsConfidentialityNormativeHealth careGood practicePsychologyPatient confidentialityInternet privacyPublic relationsEngineering ethicsPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

There is a paucity of published research and normative standards to guide health care providers in managing issues related to children's confidentiality. In this article, we examine challenges regarding the respect for confidentiality with children and youth in health care and offer guiding principles for clinical practice. We present an ethical framework and practice recommendations for: (a) respecting confidentiality for children who have decision-making capacity (as legally defined in different jurisdictions) and (b) recognizing some degree of respect for confidentiality among children who do not have decision-making capacity. This article will help incite additional analyses and research that can further refine the normative and practice standards proposed here.

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)0.074
metaresearch head score (Gemma)0.132
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.074
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.132
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.042
Scholarly communication0.0120.014
Open science0.0020.014
Research integrity0.0090.015
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 head0.030
GPT teacher head0.381
Teacher spread0.351 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations24
Published2018
Admission routes2
Has abstractyes

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