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Record W90049816 · doi:10.1093/pch/16.4.223

Ethical participation of children and youth in medical education

2011· article· en· W90049816 on OpenAlexafffund
RI Hilliard, Conrad V. Fernandez, Ellen Tsai

Bibliographic record

VenuePaediatrics & Child Health · 2011
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsCanadian Paediatric Society
FundersCollege of Family Physicians of CanadaRoyal College of Physicians and Surgeons of Canada
KeywordsStatement (logic)ConfidentialityPosition statementVariety (cybernetics)Medical educationEthical issuesPsychologyMedicinePosition (finance)Family medicineEngineering ethicsPolitical scienceLawEngineeringComputer science

Abstract

fetched live from OpenAlex

Children and youth (referred to as 'children' in the present statement), whether actual patients or volunteers, frequently participate in medical education. The present position statement discusses the numerous ethical challenges that may arise including respect for persons, truth telling and confidentiality. The statement provides guidelines that may be helpful to educators from a wide variety of disciplines.

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)0.048
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.254

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.065
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0110.015
Scholarly communication0.0060.004
Open science0.0020.009
Research integrity0.0130.014
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.364
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 designTheoretical or conceptual
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

Citations11
Published2011
Admission routes2
Has abstractyes

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