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Record W3045173868 · doi:10.1123/jsep.2019-0280

Effects of Peer Encouragement on Efficacy Perceptions and Physical Performance in Children

2020· article· en· W3045173868 on OpenAlexaff
Kira L. Innes, Jeffrey D. Graham, Steven R. Bray

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2020
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychologySalience (neuroscience)PerceptionTask (project management)Social psychologyDevelopmental psychologySelf-efficacyPeer groupPeer reviewCognitive psychology

Abstract

fetched live from OpenAlex

Social interactions are theorized to inform relation-inferred self-efficacy (RISE), which, in turn, may influence self-efficacy and behavior. This study investigated the effects of peer encouragement on RISE, task self-efficacy, and physical performance. Children (N = 84) were assigned to dyads and randomized to provide peer encouragement to one another or not (control group). Participants completed two endurance handgrip trials, separated by a cognitively demanding task intended to induce mental fatigue and increase the salience of the peer encouragement manipulation. Participants in the experimental group exchanged words of encouragement prior to the second endurance trial, whereas those in the control group did not. The peer encouragement group reported higher RISE and showed increased performance across trials compared with controls. Providing peer encouragement prior to a challenging physical task was associated with more positive RISE perceptions and improved physical performance.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.365
Teacher spread0.341 · 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 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

Citations9
Published2020
Admission routes1
Has abstractyes

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