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Record W3028251215 · doi:10.1093/jpepsy/jsaa026

Sustained Reductions in Children's Risk Taking from Peer-Communicated Behavioral Safety Norms

2020· article· en· W3028251215 on OpenAlexafffund
Barbara A. Morrongiello, Emily Weinberger, Mackenzie Seasons

Bibliographic record

VenueJournal of Pediatric Psychology · 2020
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsMoodPsychologyPeer groupDevelopmental psychologyNorm (philosophy)Social psychologyClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: This research examined whether the positive effects of a peer-communicated social norm that reduces risk-taking behaviors persist over time and if a reminder of this peer-communicated safety message has any impact on this outcome. METHODS: Positive mood in 7- to 9-year olds was induced experimentally and risk taking intentions and behaviors were measured when the child was in a positive and neutral mood state and after they had been exposed to either a safety or neutral peer-communicated social norm message. A few weeks later, half of the participants who experienced the safety social norm message were exposed to a reminder of this message via a slogan and risk-taking measures were taken again when in a heightened positive mood state. RESULTS: Exposure to a safety norm successfully counteracted the increase in risk taking associated with a positive mood state. These effects persisted for several weeks regardless of whether the children were exposed to a reminder. CONCLUSION: Manipulating peer social norms holds promise as an approach to produce reductions in children's risk taking and these effects persist at least over several weeks.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.072
GPT teacher head0.420
Teacher spread0.349 · 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.

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
Published2020
Admission routes2
Has abstractyes

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