Review of "Toronto’s Fighting 75th in the Great War, 1915-1919" by Timothy J. Stewart
Bibliographic record
Abstract
Canadian forces generally enjoy a good reputation among students of the Great War.That reputation is well deserved and owes its endurance to fine works written by thoughtful historians.Timothy J. Stewart's Toronto's Fighting 75th in the Great War, 1915War, -1919, , is a fitting addition to that historiography.The 75th (Mississauga) Battalion was recruited in Toronto, and as part of the 11th Brigade, 4th Division.It served in combat in France and Belgium and afterward was re-designated the Toronto Scottish Regiment.While veterans and historians have written histories of many other Canadian Great War formations, a history of the 75th Battalion was lacking.In writing this book, Stewart seeks to tell "the story of a Great War fighting battalion, its major personalities, and the battles in which it fought, all in the context of the 11th Brigade, the 4th Division, and the Canadian Corps" (p.xvii).The author is a high school history teacher and the curator of the Toronto Scottish Regiment's Museum.As curator of the museum, Stewart has access to the records and artifacts associated with the battalion.In addition to official records, Stewart's sources include memoirs, letters, diaries, newspaper accounts, and secondary historical works.In the first part of his book Stewart covers the history of the militia units based in Toronto, from 1901 to 1915, which were the precursors of the 75th Battalion.These include the Toronto Mounted Rifles, the 9th Toronto Light Horse, and the 9th Mississauga Horse.The second and major section of the book covers the battalion's World War I service.A final section covers the 75th Battalion from
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".