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Record W4398145731 · doi:10.1136/ip-2023-045087

Children’s participatory needs in injury prevention: reflections on supporting children’s right to invite and comfort in discussing sensitive topics

2024· article· en· W4398145731 on OpenAlexafffundabout
Michelle E. E. Bauer, Ian Pike

Bibliographic record

VenueInjury Prevention · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsSpinal Cord Injury BCUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsCitizen journalismHuman factors and ergonomicsPoison controlSuicide preventionInjury preventionOccupational safety and healthPsychologyEngineeringSociologyForensic engineeringMedicineMedical emergencyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Child-centred approaches in injury prevention emphasise the importance of practising bidirectional communications and decentring researcher-child power relations to support children's participation in research. To date, however, a dearth of scholarship offers methodological reflections on how to bolster children's feelings of comfort in discussing sensitive topics such as their injury experiences. GOAL: Drawing from lessons we learnt working with children in a low-income to mid-income neighbourhood in Vancouver, Canada, we discuss the ways in which our strategies to support their participation succeeded in, and at times fell short of, supporting their participatory needs. DISCUSSION: Our discussions focus attention on two important areas for consideration in future injury prevention studies: (1) Children's inclusion in research and the demand for them to share experience and (2) supporting children's right to invite and comfort in discussing sensitive topics such as injury experiences. We discuss the benefits of making research fun for children and being sensitive to their needs at preliminary recruitment and data collection stages. IMPLICATIONS: These discussions can strengthen researchers' work with children by helping them to reflect on strategies that can bolster their desire to participate and feel comfortable sharing perspectives.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.266
GPT teacher head0.595
Teacher spread0.329 · 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 teacher head, 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

Citations0
Published2024
Admission routes3
Has abstractyes

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