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The Relatedness to Others in Physical Activity Scale: Evidence for Structural and Criterion Validity

2010· article· en· W2170994672 on OpenAlexaff
Philip M. Wilson, Enrique Garcíá Bengoechea

Bibliographic record

VenueJournal of Applied Biobehavioral Research · 2010
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsMcGill UniversityBrock University
Fundersnot available
KeywordsPsychologySocial connectednessConfirmatory factor analysisShort FormsCriterion validityStructural equation modelingScale (ratio)Competence (human resources)Concurrent validityAutonomyTest validityDevelopmental psychologyPsychometricsSocial psychologyClinical psychologyConstruct validityStatisticsInternal consistencyMathematics

Abstract

fetched live from OpenAlex

The purpose of this study was to test the structural and criterion validity of scores derived from the Relatedness to Others in Physical Activity Scale (ROPAS). The participants (n1 = 893; n2 = 522) completed the ROPAS in addition to demographic questions (study 1) and well‐being indicators (study 2) using cross‐sectional, nonexperimental surveys. Confirmatory factor analysis (study 1) supported the tenability of a 6‐item ROPAS measurement model that was invariant across gender. Higher ROPAS scores were associated with greater perceived autonomy and competence and greater well‐being (study 2). Overall, these findings suggested the ROPAS displays a number of psychometric properties that render the instrument useful for investigating issues of belonging and connectedness with others in global physical activity settings.

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)0.006
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 score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.253
GPT teacher head0.518
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

Citations50
Published2010
Admission routes1
Has abstractyes

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