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Record W4315436071 · doi:10.1080/02701367.2022.2125927

Development of ELIP to Assess Physical Literacy for Emerging Adults: A Methodological and Epistemological Challenge

2023· article· en· W4315436071 on OpenAlexaff
Joseph Gandrieau, Christophe Schnitzler, John Cairney, Richard Keegan, Will Roberts, Peter Bentsen, Dean Dudley, Raymond Kim Wai Sum, Fotini Venetsanou, Chris Button, Sylvain Turcotte, Félix Berrigan, Marc Cloes, James Rudd, Vassiliki Riga, Alexandre Mouton, Jana Vašíčková, Joël Blanchard, Léa Mekkaoui, Thibaut Derigny, N. Franck, R-M. Repond, Mojca Markovic, Claude Scheuer, François Potdevin

Bibliographic record

VenueResearch Quarterly for Exercise and Sport · 2023
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsOperationalizationCognitionPsychologyLiteracyDelphi methodReliability (semiconductor)Cognitive skillValuation (finance)Cognitive psychologyApplied psychologyComputer sciencePedagogyArtificial intelligenceEpistemology

Abstract

fetched live from OpenAlex

Purpose: Following increased interest in physical literacy (PL), development of appropriate tools for assessment has become an important next step for its operationalization. To forward the development of such tools, the objective of this study was to build the foundations of the Évaluation de la Littératie Physique (ELIP), designed to help reduce existing tensions in approaches to PL assessment that may be resulting in a low uptake into applied settings. Methods: We followed two steps: (1) the development of the first version of ELIP by deploying a Delphi method (n = 30); and (2) the modification of items through cognitive interviews with emerging adults (n = 32). Results: The expert consensus highlighted four dimensions of PL to be assessed—physical; affective; cognitive; and social—with new perspectives, including a preference for broad motor tests over fitness. Conclusion: Results offer new insights into the assessment of emerging adults’ PL, but ELIP still requires further work concerning validity, reliability, and sensitivity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.225
GPT teacher head0.479
Teacher spread0.254 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

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