Falstaff and Rodion: Programmatic Compositional Study of Two Characters of Fiction
Bibliographic record
Abstract
The goal of this thesis is to explore specific aspects of creativity from the point of view of the composer. I have found, in looking back over twenty-plus years of writing music, that I have had a tendency to gravitate towards attempting to represent or pay tribute to real people and places from my life experience using an impressionistic compositional approach. \nWhile using a singular approach can lead to an extensive exploration of a discipline and lead to a recognizable and, therefore, marketable style by which a composer becomes known, I felt that a journey into a different concept could help broaden my own creative perspective. \nTo that end, this thesis involves the composition of two pieces using a programmatic approach intended to represent the narrative arc of two fictional characters from Dostoevsky's Rodion Raskolnikov and Shakespeare's Sir John Falstaff. To embody someone who only exists in the imagination of his own creator, I feel that using a programmatic approach works better in bringing out the subject.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".