The Elements of Contemporary Turkish Composers’ Solo Piano Works Used in Piano Education
Bibliographic record
Abstract
It is thought that to be successful in piano education it is important to understand how composers composed their solo piano works. In order to understand contemporary music, it is considered that the definition of today’s changing music understanding is possible with a closer examination of the ideas of contemporary composers about their artistic productions. For this reason, the qualitative research method was adopted in this study and the data obtained from the semi-structured interviews with 7 Turkish contemporary composers were analyzed by creating codes and themes with “Nvivo11 Qualitative Data Analysis Program”. The results obtained are musical elements of currents, styles, techniques, composers and genres that are influenced by contemporary Turkish composers’ solo piano works used in piano education. In total, 9 currents like Fluxus and New Complexity, 3 styles like Claudio Monteverdi, 5 techniques like Spectral Music and Polymodality, 5 composers like Karlheinz Stockhausen and Guillaume de Machaut and 9 genres like Turkish Folk Music and Traditional Greek are reached. It is thought that the results will contribute to the field because it will cause a better understanding in the artistic viewpoints of contemporary composers, as well as being a step for the piano and music educators and the students who have studied academic piano education in order for them to be able to understand the contemporary music.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".