Bibliographic record
Abstract
Attention is drawn to the place of art education in the life of the outstanding conductor and composer Oleksandr Koshyts. Periodization of the artist’s pedagogical activity before emigration (in Ukraine) and abroad (in the USA and Canada). The features and values that were characteristic of Oleksandr Koshyts as a teacher are highlighted: patriotic dominant, strength of will and ability to master someone else’s will, deep concentration, great knowledge in the fields of philosophy, theology, literature, history, archeology, folklore, colossal musical training, knowledge of foreign languages (including English), good knowledge of psychology, which helped him become a great connoisseur of the human soul and its emotional manifestations, audience, love and respect for students, consonant work to improve their professional level, which contributed to its formation as a teacher-innovator. The components of his charismatic personality are established: 1) psychological and physical personalities of qualities, traits, abilities and possibilities; 2) the image of the leader; 3) communicative aspects of influence (speaking skills, interaction with people, methods of influencing them, public speaking, charismatic leader as a destroyer of customs and creator of rituals; 4) motivation of the leader (pragmatic motives, motives of metaphysical, missionary level, mission).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".