Flu on the Front: the Effects of the Influenza Pandemic of 1918-1919 on the 15th Reserve and 46th Infantry Battalions, Canadian Expeditionary Force
Bibliographic record
Abstract
This study is an examination of the effects of the first two waves of the Influenza Pandemic of 1918-1919 on the Canadian Expeditionary Force in Europe during the final months of the First World War. Using a case-study approach, the study analyzes the experiences of the 15th Canadian Reserve Battalion (Saskatchewan) in England and the 46th Canadian Infantry Battalion (South Saskatchewan) in France from April to 11 November 1918. While the comparison of these two battalions’ experiences is useful to see the how the Canadian Army Medical Corps reacted and responded to the outbreak of pandemic influenza in both locations, it also highlights the impact that the pandemic had on the reinforcement stream in 1918, and demonstrates the greater cost of conscription during the final months of the war. This thesis argues that that the Influenza Pandemic of 1918-1919 affected the Canadian Expeditionary Force’s Hundred Days Campaign in a way that, until now, has not been recognized. Additionally, it argues that the 15th Reserve Battalion was not to blame for bringing pandemic influenza to Bramshott Camp in the fall of 1918, and that the Canadian Army Medical Corps reacted to the outbreak as effectively as possible. Finally, it highlights the experiences of men from Saskatchewan and recounts the stories of soldiers who died of pandemic influenza.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.032 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".