Are there differences in practice depending on the instrument played?
Bibliographic record
Abstract
There has been little research on instrument differences in the length and nature of instrumental practice or how these may interact with level of expertise. This paper aimed to address this issue. A total of 3,325 young people ranging in level of expertise from beginner to the level required for entry to higher education conservatoire completed a questionnaire which consisted of a number of statements relating to time spent practicing, practicing strategies, organization of practice, and motivation to practice with a seven-point rating scale. Data were analyzed in relation to nine levels of expertise. Factor analysis revealed seven factors which were used to make comparisons between those playing different classical instruments. The findings showed that those playing keyboard instruments practiced the most, followed by strings, brass, and woodwind. There were relatively few statistically significant instrument differences in practice strategies. Where there were differences it was the woodwind players who tended to adopt less effective strategies. There were some interactions between level of expertise and practice which generally showed no clear patterns suggesting complexity in the development of musical expertise in relation to different instruments. The findings are discussed in terms of possible reasons for these differences.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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 teacher head, 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".