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Record W2056586103 · doi:10.1177/0022429410386965

Performance Stress and the Very Young Musician

2010· article· en· W2056586103 on OpenAlexaff
Hélène Boucher, Charlene Ryan

Bibliographic record

VenueJournal of Research in Music Education · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsMcGill University
Fundersnot available
KeywordsAnxietyPsychologyDevelopmental psychologyAffect (linguistics)Stress (linguistics)Clinical psychologyCommunicationPsychiatry

Abstract

fetched live from OpenAlex

Performance anxiety is a common experience among musicians. Recent studies have found it to be an issue not only for adult performers but also for developing musicians as early as third grade. The question as to its developed or innate nature led to the present inquiry pertaining to young children’s responses to performance situations. Sixty-six 3- and 4-year-olds taking group music lessons that culminated in two concerts served as participants. Self-report of anticipatory anxiety, cortisol secretion, and observation of anxious behaviors were the primary measures. Results indicated that young children did experience anxiety with respect to music performances and that responses seemed to have both innate and developed components. Children with prior performing experience reported less anticipatory anxiety, but had higher cortisol levels, than those without prior experience. Additionally, performance location seemed to play a role in children’s anxiety responses. Those who were familiar with their performance environment responded with less anxiety than those who were not. Overall, second performances within a short time frame elicited much lower anxiety responses than initial performances. Findings pertaining to performance location and second performances appear to have direct pedagogical implications, which may help to reduce performance stress in young children.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.093
GPT teacher head0.339
Teacher spread0.246 · 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

Citations85
Published2010
Admission routes1
Has abstractyes

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