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Record W2911972856 · doi:10.1080/00336297.2019.1570855

Antecedents of Physical Literacy: George Herbert Mead and the Genesis of the Self in Play and Games

2019· article· en· W2911972856 on OpenAlexaff
Danny Rosenberg

Bibliographic record

VenueQuest · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsBrock University
Fundersnot available
KeywordsGeorge (robot)PsychologyLiteracySociologySocial psychologyPedagogyArtArt history

Abstract

fetched live from OpenAlex

Physical literacy has gained worldwide prominence over the last decade by re-conceptualizing primarily the meaning of physical education. British educator Margaret Whitehead is the most famous proponent of this expression and expositor of its philosophical foundation and value. As such, physical literacy rejects dualism, is buttressed by monism, phenomenology, and existentialism, and provides insights regarding perception, embodiment, and human existence. Two aspects of physical literacy, relevant to this inquiry, are the development of a sense of self and the notion of universality. Both these concepts were addressed by George Herbert Mead over 80 years ago in relation to the genesis of the self in play and the “generalized other” in games as expounded in his seminal work, Mind, Self, & Society. A comparison of the concept of physical literacy and Mead’s thought on the development of the self in physical activity will reveal that the antecedents of physical literacy offer it a useful critique.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.055

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 studies0.0060.025
Scholarly communication0.0030.005
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.417
Teacher spread0.396 · 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 designTheoretical or conceptual
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

Citations3
Published2019
Admission routes1
Has abstractyes

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