Music performance anxiety in children 9−12 years old in a music program
Bibliographic record
Abstract
Abstract Music‐intensive school program are one way of enhancing arts‐education in public schools. Elementary school students enrolled in a music‐intensive program are exposed to several stress factors that could contribute to development of music performance anxiety (MPA). This study aims to describe MPA manifestations as reported by 164 students from 9 to 12 years of age taking part in a music‐intensive school program, and to identify what may contribute to its development. Data were collected using a sociodemographic questionnaire, and the French version of the Music Performance Anxiety Inventory for Adolescents. Although it was expected that being involved in an intensive music program would bring students to report higher levels of MPA, results showed moderate levels of MPA. In addition, girls reported significatively more manifestations of MPA than boys. The MPA level also vary according to the origin of the registration in the program (child's request or parents' suggestion), and the cycle. Indeed, cycle 2 students reported significantly less MPA than cycle 3 students when the request to participate in the music‐intensive program came from the child. Findings provide useful key points that should be considered for both practitioners and researchers.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".