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Record W4402556915 · doi:10.1177/02557614241279723

Oboe educators’ perspectives on playing-related injury, Part I: Lived experience and perceptions surrounding injury

2024· article· en· W4402556915 on OpenAlexaff
Heather M. Macdonald, Christine Guptill

Bibliographic record

VenueInternational Journal of Music Education · 2024
Typearticle
Languageen
FieldMedicine
TopicMusicians’ Health and Performance
Canadian institutionsUniversity of OttawaMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsOboePerceptionPsychologyPedagogyArt

Abstract

fetched live from OpenAlex

Music students experiencing the potentially debilitating effects of playing-related injury (PRI) often first turn to their music teachers for help. This paper aims to document music instructors’ lived experience and perceptions surrounding PRI and better understand how teachers currently support students’ musculoskeletal health. Using a qualitative description approach, in-depth interviews with 10 oboe teachers (7 male, 3 female) documented their lived experience with or without injury and perceptions of PRI. Self-identified uninjured participants ( n = 5) described PRI-adjacent and non-PRI problems which elicited empathy for injured musicians, and self-reflective practices that contributed to better health. Injured participants described varied relationships to their pain, including pain as a source of guilt, distress, learning, and growth, and described diverse coping mechanisms including physical therapy, medication, mindfulness, and self-experimentation. Participants’ observations and experiences of PRI influenced their teaching, and several described seeking greater efficiency in students’ instrument set-up and body use. Resources for injured musicians were perceived to be difficult to access due to financial constraints, unawareness, jargon-filled language, and misinformation. These results suggest a need for more outreach from performing arts health professionals connecting music teachers, often the first point of contact for injured students, with high-quality resources which support student wellbeing.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.391
Teacher spread0.354 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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