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Record W2096581761 · doi:10.1598/jaal.48.3.4

The Use of Alternative Texts in Physical Education

2004· article· en· W2096581761 on OpenAlexaff
Paul B. Marlett, Christine J. Gordon

Bibliographic record

VenueJournal of Adolescent & Adult Literacy · 2004
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsUniversity of CalgaryCanadian Wood Council
Fundersnot available
KeywordsFeelingLiteracyPhysical educationVariety (cybernetics)PsychologyPedagogySubject (documents)CognitionMathematics educationSocial psychologyComputer science

Abstract

fetched live from OpenAlex

Body and mind must be seen as inseparable in physical education; movement and activity as well as thinking and feeling should be part of students' lives. By expanding the definition of text to include a variety of printed, visual, oral, electronic, and other types of texts, physical education teachers can incorporate literacy activities to enhance affective and cognitive transactions during physical education. These activities can also make connections to other subject areas, thereby promoting learning and making movement a meaningful part of daily living. In addition, these tenets of content literacy contribute to making physical education a mindful (thinking) and feeling discipline as well as an active living one. Under the umbrella of a content literacy philosophy, this article presents examples of several alternative texts (i.e., poetry, sculpture, picture) to use in physical education. It then discusses the use of such alternative texts and appropriate teaching strategies for building body image, providing outdoor education, and promoting the study of physical exertion.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.072
GPT teacher head0.474
Teacher spread0.402 · 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 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

Citations7
Published2004
Admission routes1
Has abstractyes

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