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Is Recess an Achievement Context? An Application of Expectancy-Value Theory to Playground Choices

2009· article· en· W39116067 on OpenAlexfundvenueno aff
Nancy Spencer-Cavaliere, Janice Causgrove Dunn, Emily Jane Watkinson

Bibliographic record

VenueAlberta Journal of Educational Research · 2009
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Alberta
KeywordsExpectancy theoryPsychologyContext (archaeology)Value (mathematics)Context effectAcademic achievementSocial psychologyMathematics educationDevelopmental psychologyStatisticsMathematics

Abstract

fetched live from OpenAlex

This study investigated the application of an expectancy-value model to children’s activity choices on the playground at recess. The purpose was to test the prediction that expectancies for success and subjective task values are related to decisions to engage in specific recess activities such as climbing, playing soccer, or skipping rope. Participants included 242 children in grades 1-4 from five schools. Participation in playground activities was assessed using the Activities for Daily Living in Physical Play (ADL-PP) (Watkinson et al., 2001). Task-specific expectancies and values were measured on the playground activities contained in the ADL-PP. The results indicated that children’s perceptions of competence were significantly higher on playground skills that they had identified as most important compared with least important (p

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)0.004
metaresearch head score (Gemma)0.021
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 score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.097
GPT teacher head0.492
Teacher spread0.395 · 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

Citations2
Published2009
Admission routes2
Has abstractyes

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