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Record W4395012664 · doi:10.1080/10413200.2024.2342323

Four domains for development for all (4D4D4All): A holistic, physical literacy framework

2024· article· en· W4395012664 on OpenAlexafffund
Jennifer P. Agans, Melanie I. Stuckey, John Cairney, Dean Kriellaars

Bibliographic record

VenueJournal of Applied Sport Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of ManitobaNational Circus School
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyHolistic educationLiteracyPhysical educationDevelopmental psychologyMathematics educationPedagogy

Abstract

fetched live from OpenAlex

People participate in many different types of physical activity, both daily and across their life span, but research on human movement is often siloed by type (sport, exercise, active transportation, etc.). Models developed for understanding participation in specific types of physical activity remain useful in those contexts, but are insufficient for describing, explaining, or enhancing movement at the individual or societal level. Physical literacy has the potential to serve this purpose, but its current application does not fulfill its potential for holistic and inclusive promotion of movement. This paper therefore introduces a new framework for physical literacy, Four Domains for Development for All (4D4D4All). This framework highlights the interrelations among the physical, psychological, social, and creative aspects of movement, and emphasizes how development across all four domains can be supported through the interrelations of individuals and their contexts. In this paper, we introduce the 4D4D4All framework and present ideas for its application in research and practice. Specifically, this individualized, holistic, and inclusive approach to physical literacy is an alternative to models that emphasize the production of podium-driven athletes or focus on meeting physical activity guidelines, and is therefore better suited to facilitate the development of flourishing active people.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.038
GPT teacher head0.381
Teacher spread0.343 · 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.

Study designNot applicable
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

Citations18
Published2024
Admission routes2
Has abstractyes

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