New Brunswickâs Artillery Goes to War, 1914-1915
Bibliographic record
Abstract
This case study of artillery units from New Brunswick examines the role of the M ilitia in Canada's mobilisation for the F irst World War, from August 1914 through the Second Battle of Ypres in A p ril-May 1915, the Canadian fo rces' first major combat.It shows that the M ilitia artillery in the province provided a strong basis, in organisation and in the considerable number of serving and form er members, for both emergency home defence measures and raising units for overseas service.The piece also demonstrates the strong provincial identity of the gunners.The largest unit, the 3rd Regiment of Saint John, made a determined effort to raise "New Brunsw ick" units for overseas service, and succeeded because of its ability promptly to provide capable personnel in fully sufficient numbers.N ew B runsw ick's m ilitia artillery units played a significant but little-known role in the First World War for home defence and in recruiting and training personnel for overseas service.Published work on Canada's military effort of 1914-18 has rightly given priority to the overseas corps and particularly to the infantry.Treatment of the corps artillery has been less extensive, and there has been little work on the units of the Militia in Canada-the nation's traditional military force.The present article shows how peacetime organisation enabled New Brunswick's artillery units to make an early contribution -notably at the Second Battle of Ypres, the Canadian division's first
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.030 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".