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Fifteen-minute consultation: Guide to communicating with children and young people

2021· article· en· W3216460048 on OpenAlexafffund
Gail Davison, Richard Conn, Martina Kelly, Andrew Thompson, Tim Dornan

Bibliographic record

VenueArchives of Disease in Childhood Education & Practice · 2021
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsUniversity of Calgary
FundersHospital for Sick Children
KeywordsActive listeningHealth professionalsPsychologyHealth careNursingMedical educationPublic relationsMedicineCommunicationPolitical science

Abstract

fetched live from OpenAlex

This article suggests communicative steps and strategies to help healthcare professionals achieve the ideals of child-centred care, which place children and young people at the centre of policy and practice. For those with 15 s, not 15 min, our suggestions can be summarised like this: help children be active agents in their own care by asking, listening well, being curious and explaining things clearly in an accessible but not condescending way.

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)0.004
metaresearch head score (Gemma)0.011
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.089
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0030.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0890.060

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 head0.016
GPT teacher head0.383
Teacher spread0.367 · 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
GenreMethods

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

Citations14
Published2021
Admission routes2
Has abstractyes

Explore more

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