Byngâs and Currieâs Commanders: A Still Untold Story of the Canadian Corps
Bibliographic record
Abstract
In 1915, the Canadian Corps was little more than a rabble of enthusiastic amateurs. Yet by 1917-18, it had become an accomplished professional fighting force, one characterized by Denis Winter as “much the most effective unit in the BEF” and by Shane Schreiber as “the shock army of the British Empire.” While Canadian military historians have studied this evolution extensively few have examined the decisive element in the transformation—the development of a cadre of proficient senior combat officers. No one questions Currie’s status as Canada’s best fighting general, but of the supporting team he and his predecessor, General Byng, assembled we know precious little. Who, then, were the men commanding the Corps’ four divisions, 12 infantry brigades and supporting machine gun and artillery units—the senior officers whose abilities as trainers and fighters were integral to the CEF’s battlefield success?
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.073 | 0.030 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".