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Record W4307042910 · doi:10.1080/15290824.2022.2125977

Safe Dance Practice Knowledge, Beliefs, and Behaviors among Alberta Dance Teachers

2022· article· en· W4307042910 on OpenAlexaffabout
Jillian L. Ball, M. Critchley, Amanda M. Black, Sarah Kenny

Bibliographic record

VenueJournal of Dance Education · 2022
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsDanceDance educationPsychologyStudioMedical educationPedagogyMedicineVisual artsArt

Abstract

fetched live from OpenAlex

Dance teachers are ideally positioned to implement safe dance practices and injury prevention strategies for their students. However, to date, it is unclear whether these safe dance practices are being utilized and implemented by teachers in dance schools and private studios. To this end, we aimed to understand dance teachers’ knowledge, beliefs, and behaviors related to safe dance practice and dance-related injury by surveying a sample of 73 dance instructors teaching primarily in urban centers. While general knowledge is high, some teachers reported gaps in their understanding of injury risk. Most common barriers to implementing safe dance practices were insufficient time (20/52 [38%]), lack of knowledge/training (11/52 [21%]) and no student interest (10/52 [19%]). Addressing these barriers with dance teacher training, inclusive of safe dance practice principles, is essential to ensuring the safety and well-being of dance student populations.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.980

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.011
GPT teacher head0.333
Teacher spread0.322 · 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 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

Citations2
Published2022
Admission routes2
Has abstractyes

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