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Record W4387711864 · doi:10.29173/mm17

Inspired by Dance: A Future for Kinesiology

2023· article· en· W4387711864 on OpenAlexafffundvenueabout
Emily Noton

Bibliographic record

VenueMovement Matters · 2023
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsDanceKinesiologyDance educationContext (archaeology)RecreationCurriculumPhysical educationThe artsMultidisciplinary approachPedagogyVisual artsSociologyPsychologyMedical educationArtPolitical scienceMedicineSocial scienceHistory

Abstract

fetched live from OpenAlex

Although the beginning of North American post-secondary level dance education is often traced to physical education, dance programs have since migrated to Fine Arts Faculties. Despite these developments, dance has not entirely disappeared from physical education contexts which are now often under the umbrella of kinesiology. This context can hold new possibilities for dance-inspired movement education. In this paper, I, as a trained dancer with a research degree in the broad field of kinesiology, reflect upon my experiences of designing an undergraduate dance-inspired movement fundamentals course in a multidisciplinary, research-led Faculty of Kinesiology, Sport, and Recreation in Canada. I further contemplate possible positive implications of including dance research, dance practices, and dance education in this context and the undergraduate kinesiology curriculum.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.001

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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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

Citations1
Published2023
Admission routes4
Has abstractyes

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