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Record W2307816807 · doi:10.1080/03004430.2015.1100175

Using a picture book to gain assent in research with young children

2015· article· en· W2307816807 on OpenAlexafffund
Angela Pyle, Erica Danniels

Bibliographic record

VenueEarly Child Development and Care · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversity of TorontoInstitute for Christian Studies
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyCompetence (human resources)Perspective (graphical)Dissenting opinionDevelopmental psychologyInformed consentPedagogyMedical educationSocial psychologyAlternative medicineMedicine

Abstract

fetched live from OpenAlex

There has been a shift in perspective from viewing children as adults-in-the-making to individual agents, possessing the right and the competence to meaningfully participate in research. Many researchers are striving to obtain informed assent from young children prior to their participation in research. Methodological concerns have been presented which differ from traditional consent for adults, many related to language and process issues. In light of these, an assent protocol utilising a picture book that included photographs of young children engaged in research activities was developed to help capture children's interest and aid in their understanding of the research project. Children in two separate studies were presented with the book and demonstrated their understanding through engaging in meaningful discussion about the research process, assenting, and dissenting to participate. Important process considerations are discussed, along with the appropriateness of using a picture book to gather informed assent from young children.

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)0.025
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0030.007
Open science0.0010.007
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0430.017

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 head0.141
GPT teacher head0.386
Teacher spread0.245 · 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 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

Citations28
Published2015
Admission routes2
Has abstractyes

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