Tuning into musicians’ wellbeing: Research on music performance anxiety (MPA)
Bibliographic record
Abstract
Tuning into musicians' wellbeing: Research on music performance anxiety (MPA) The Music and Mental Health Research Clinic (MMHRC) at the University of Ottawa's Institute of Mental Health Research (IMHR) at The Royal is investigating how to reduce music performance anxiety (MPA) and the benefits of specific coping strategies for musicians. The audience cheers, and smiles are on every face. The music performance was incredible; it emotionally moved the audience, got their toes tapping, and made them forget their worries. On the other hand, the musicians are thinking about the note they missed or their tempo not being quite perfect. The audience does not see the musicians worrying before the performance, the state of anxiety during the performance, or the negative rumination that will occur afterwards. Biologically wired with an innate tendency to default to negative assumptions to avoid dangerous situations, our bodies react to stressors as if our lives are at stake (Baumeister, 2001; Rozin & Royzman, 2001; Ito & Cacioppo, 2005). This negativity bias is a key reason why changing our habits, behaviours, and thought patterns is so challenging. It often results in automatic negative thoughts, such as underestimating available opportunities and resources, and increased sensitivity to perceived threats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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; both teacher heads agree on what is shown here.
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".