Gender differences in musical motivation at different levels of expertise
Bibliographic record
Abstract
Recently, models have been developed that recognise the complexity of motivation. These set out the interactions that occur between environmental (cultural, institutional, familial, educational) and internal factors (cognition and affect) enhancing or reducing motivation. Despite this we know very little about gender differences in motivation in relation to playing an instrument. The current study aimed to address this issue, exploring gender differences in motivation and whether these changed as expertise developed. A total of 3325 children ranging in level of expertise from beginner through to Grade 8 level in independent instrumental music examinations completed a questionnaire that included a seven-point Likert scale with statements exploring different aspects of motivation. A principal components analysis was undertaken and six factors emerged: support and social affirmation; social life and enjoyment of musical activities; enjoyment of performing; self-beliefs; enjoyment of lessons, playing and practise; and disliking practise. The only statistically significant gender difference was in relation to self-beliefs with the boys consistently scoring higher. Further research is needed to establish why this is the case. The findings have major implications for education.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".