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Record W2120776588 · doi:10.1093/jpepsy/jsu100

Exploring Relations Between Positive Mood State and School-Age Children’s Risk Taking

2014· article· en· W2120776588 on OpenAlexafffund
Barbara A. Morrongiello, Julia Stewart, Kristina Pope, Ekaterina Pogrebtsova, Karissa-June Boulay

Bibliographic record

VenueJournal of Pediatric Psychology · 2014
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsMoodPsychologyDevelopmental psychologyTraitClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine whether children engage in greater risk taking when in a positive versus neutral mood state, and whether positive urgency trait relates to risk taking. METHODS: Positive mood in 7-10-year-old children was induced experimentally, and children's risk-taking intentions and actual behaviors were measured when the child was in a positive and neutral mood state. RESULTS: Within-person comparisons revealed that children showed greater risk-taking intentions and actual risk behaviors when in a positive mood state compared with a neutral one. Positive urgency was associated with greater risk taking when in a positive mood state, and this effect was stronger in the actual risk taking than intentions to risk take task. CONCLUSIONS: Mood state affects children's risk taking. Positive mood is associated with greater risk taking in elementary-school children, and those high in positive urgency are especially likely to show this effect. Implications for injury prevention are discussed.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.062
GPT teacher head0.357
Teacher spread0.295 · 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

Citations16
Published2014
Admission routes2
Has abstractyes

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