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Can child injury prevention include healthy risk promotion?

2014· review· en· W2142675288 on OpenAlexafffundabout
Mariana Brussoni, Sara Brunelle, Ian Pike, Ellen Beate Hansen Sandseter, Susan Herrington, Heather Turner, Scott Belair, Louise Logan, Pamela Fuselli, David J. Ball

Bibliographic record

VenueInjury Prevention · 2014
Typereview
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsParachuteUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BCChild and Family Research Institute
KeywordsRecreationOccupational safety and healthInjury preventionSuicide preventionPoison controlPromotion (chess)Multidisciplinary approachHuman factors and ergonomicsMedicinePublic relationsPsychologyEngineeringMedical educationPolitical scienceEnvironmental healthPathology

Abstract

fetched live from OpenAlex

To reflect on the role of risk-taking and risky play in child development and consider recommendations for the injury prevention field, a symposium was held prior to the November 2013 Canadian Injury Prevention and Safety Promotion Conference. Delegates heard from Canadian and international researchers, practitioners and play safety experts on child development, play space design and playground safety, provision of recreation, and legal and societal perceptions of risk and hazard. The presenters provided multidisciplinary evidence and perspectives indicating the potential negative effect on children's development of approaches to injury prevention that prioritise safety and limit children's opportunities for risky play. Delegates considered the state of the field of injury prevention and whether alternative approaches were warranted. Each presenter prepared a discussion paper to provide the opportunity for dialogue beyond attendees at the symposium. The resulting discussion papers provide a unique opportunity to consider and learn from multiple perspectives in order to develop a path forward.

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)0.005
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0010.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0080.002

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 head0.045
GPT teacher head0.422
Teacher spread0.377 · 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
GenreReview

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

Citations63
Published2014
Admission routes3
Has abstractyes

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