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Record W4393190390 · doi:10.1080/15290824.2023.2224799

Instructional Practices and Interpretations of Harm: A Qualitative Inquiry with 24 Competitive Dancers

2024· article· en· W4393190390 on OpenAlexaff
Aalaya Milne, Michael Atkinson, Gretchen Kerr, Ashley Stirling

Bibliographic record

VenueJournal of Dance Education · 2024
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDanceHarmThematic analysisPsychologyQualitative researchSocial psychologyPedagogySociologyVisual artsSocial scienceArt

Abstract

fetched live from OpenAlex

Recently, cases of harm have surfaced in competitive dance. The purpose of this study was to explore experiences of harm in competitive dance, specifically focusing on interactions between dancers and instructors. Semi-structured interviews were conducted with 24 competitive dancers of various gender and racial identities. Data were analyzed using reflective thematic analysis. Four themes were generated: hurtful comments, physical expressions of frustration, physical conditioning directives, and favoritism. Findings are interpreted to suggest the existence of harm in competitive dance and a need for more critical reflection on teaching practices within the competitive dance environment. Based on this research, recommendations are posed for preventing harm through the application of student-centered pedagogies.

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)0.015
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0140.016
Scholarly communication0.0050.003
Open science0.0030.008
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 head0.077
GPT teacher head0.457
Teacher spread0.381 · 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 designQualitative
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

Citations4
Published2024
Admission routes1
Has abstractyes

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