MétaCan
Menu
Back to cohort
Record W2487481876 · doi:10.1123/apaq.17.1.1

Goal Orientations, Perceptions of the Motivational Climate, and Perceived Competence of Children with Movement Difficulties

2000· article· en· W2487481876 on OpenAlexaff
Janice Causgrove Dunn

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyCompetence (human resources)PerceptionDevelopmental psychologyStructural equation modelingSocial psychologyGoal orientationPhysical educationMathematics education

Abstract

fetched live from OpenAlex

This study examined the relationships among goal orientations, perceptions of the motivational climate, and perceived competence of children with movement difficulties in Grades 4 to 6. Participants were 65 children (23 boys and 42 girls) with movement difficulties and 111 children (45 boys and 66 girls) without movement difficulties. The latter group was used only in the preliminary analyses investigating validity and reliability of instruments for use in this study. Instruments included a measure of situationally specific perceived competence, a modified version of the Task and Ego Orientation in Sport Questionnaire (Duda, 1989), and a modified version of the Perceived Motivational Climate in Sport Questionnaire (Seifriz, Duda, & Chi, 1992). Results of structural equation modeling analysis generally supported the hypothesized model of relationships, based on Nicholls’ (1989) achievement goal theory. The findings suggest that physical education classes emphasizing a mastery motivational climate may result in higher perceived competence in children with movement difficulties.

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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.273
Teacher spread0.265 · 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

Citations55
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueAdapted Physical Activity QuarterlySame topicInclusion and Disability in Education and SportFrench-language works237,207