Bibliographic record
Abstract
Military music was popular with the public because of spectacle, melody and patriotism, and in the nineteenth century this patriotism increasingly involved the Empire and imperialist sentiment. The royal family always took a particular interest in military music. But the military band was also the inspiration for the brass band. There were Imperial Marches by G.H. Dickens, Charles H. Ridee, S. Gatty Sellars and E.E. Bagley, and an Imperial Britain March by Thomas A. Chandler. John Mackenzie-Rogan gives a fascinating first-hand account of the royal and imperial occasions to which he was party. In 1907 Rogan was awarded the honorary degree of Doctor of Music by the University of Toronto. Mackenzie-Rogan was succeeded as the doyen of military music by Major Frederick Joseph Ricketts. The march entered the mainstream of art music through the opera and ballet of seventeenth-century France. Sir Arthur Sullivan and Edward Elgar both composed Imperial Marches.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.102 | 0.021 |
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".