AN ANALIZE OF AN EXAMPLE SONG IN TERMS OF INSTRUCTIONAL MUSIC COMPOSING TECHNICS
Bibliographic record
Abstract
The purpose of this study is to determine whether the school songs used in the program are appropriate in terms of composing techniques. In this respect, the school song entitled "Kirlara Dogru" was analized in terms of prosody, form and educational qualities. When the song "Kirlara Dogru" was analyzed in terms of rhythmical balance, it can be seen that the syllable "ka" at the measure 8 has long rhytmic value while it has to has short rhytnmic value. When it was analyzed in terms of word accentuation, it can be said that the syllable "lar" at the measure 4 should be in a higher pitch instead of being in a lower pitch. As for the formal analysis, the song is written in a binary form consisting of A and B phrases both of which consists of 2 two-measure-motives. The song ends with an authentic cadence. From an educational perspective, it can be said that the song is written in a one octave voice register (D-d) and the notational values used are eight, quarter, dotted quarter and dotted half notes The subject matter of the song is love of nature. As a result of these analyses it can be said that the song "Kirlara Dogru" can be a good example for Turkish Authentic School Songs. KEYWORDS; EDUCATION, MUSIC EDUCATION, SONG TEACHING, COMPOSING, PROSODY
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".