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Record W2341195449 · doi:10.20381/ruor-5611

Associations Between Domains of Physical Literacy In 8-12 Year-Old Children, by Weight Status

2016· dissertation· en· W2341195449 on OpenAlexaboutno aff
Gregory Traversy

Bibliographic record

VenueuO Research (University of Ottawa) · 2016
Typedissertation
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyPhysical educationDevelopmental psychologyPsychologyGerontologyMathematics educationPhysical therapyMedicinePedagogy

Abstract

fetched live from OpenAlex

To date, only a small number of studies have examined the results of physical literacy (PL) assessments using the Canadian Assessment of Physical Literacy (CAPL). Among these studies, none have evaluated the correlations between the four domains of PL assessed within the CAPL, nor have they evaluated whether these correlations differ depending on weight status. The current study aimed to determine the strength of associations between the four domains of PL, and compare the correlation coefficients between healthy weight and overweight/obese children. Children aged 8-12 years (n=456) were assessed using the CAPL protocol and partial correlations (controlling for age, sex, and other domain scores) were calculated between domains, for healthy weight (n=275) and overweight/obese children (n=181) separately. The results of this study show that the domains of physical competence, daily behaviour, and motivation and confidence correlate significantly with one another at similar low-to-moderate levels in both body weight groups examined (r = 0.15 to 0.38). The domain of knowledge and understanding did not correlate significantly with other domains in healthy weight participants, and only correlated significantly with physical competence in overweight/obese children (r = 0.22). Overall, the low level of correlations seen between domains in this study lends support to the psychometric architecture of the CAPL and suggests that the four domains of CAPL measure different constructs. Furthermore, the results of this study suggest that interventions aimed at improving PL in children should assess multiple domains, and do not necessarily need to be tailored based on a child’s weight status.

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)0.004
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 score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.019
GPT teacher head0.326
Teacher spread0.307 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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