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Record W4255051656 · doi:10.32920/ryerson.14652729

Children and inquiry: researchers’ reflections on research involving children

2021· preprint· en· W4255051656 on OpenAlexaffabout
Noah Kenneally

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsToronto Metropolitan UniversityEducation and Early Childhood Development
Fundersnot available
KeywordsThematic analysisResearch designQualitative researchPsychologyReflection (computer programming)Descriptive researchBest practiceDescriptive statisticsMedical educationComputer scienceSociologyMedicinePolitical scienceSocial science

Abstract

fetched live from OpenAlex

This qualitative descriptive study employed a mixed methods approach to investigate research conducted by Canadian researchers who involve children in their studies. Data collected from a questionnaire completed by thirty researchers across Canada were contextualized through seven interviews, with the goal of compiling a description of the research designs and the mechanisms of engagement used to involve children. A thematic analysis was conducted in order to explore the research designs used, how beliefs about children and childhood shape research design, and ethical and reflective practices used in research involving children. Overall, findings indicate that a wide range of research designs and mechanisms of engagement are used. Implications for practice emerging from this study suggest that researchers should choose a design approach to best suit the study’s purpose, and that deliberate and continuous reflection in design practices and implementation can promote ethical practice when conducting research involving 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)0.095
metaresearch head score (Gemma)0.125
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score0.503

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0950.125
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.006
Science and technology studies0.0390.076
Scholarly communication0.0250.017
Open science0.0060.024
Research integrity0.0080.022
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 head0.915
GPT teacher head0.746
Teacher spread0.169 · 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.

Study designQualitative
DomainMethods
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

Citations0
Published2021
Admission routes2
Has abstractyes

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