Seeing the Sound: An Exploration of the Use of Mental Imagery by Classical Musicians
Bibliographic record
Abstract
Similarities exist between the performance of musicians and athletes; both must prepare to perform at their optimal level and both experience psychological reactions to performance. Sport psychologists have begun to collaborate with performing artists to investigate the potential positive outcome of psychological skills on their performance (e.g., Connolly & Williamon, 2004; Fish et al., 2004). Mental imagery may be used for both cognitive and motivational purposes, resulting in positive performance outcomes such as learning a technically difficult piece, regulating arousal, and being confident. To explore these functions of imagery use an examination of classical musicians' use of imagery was undertaken. Music students (N = 159) completed the Functions of Imagery in Music Questionnaire (created for the purposes of this study). It was found that musicians reported employing imagery to limit distractions, recover from an error, maintain mental toughness, demonstrate confidence, and overcome mental and physical fatigue. In addition, performance majors indicated using imagery significantly more frequently to see themselves overcoming a difficult situation than non-performance majors, while voice musicians employed imagery to see goal achievement more often than instrumental musicians.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".