On the Brink of Civil War: The Canadian Government and the Suppression of the 1918 Quebec Easter Riots
Bibliographic record
Abstract
This article analyzes the Canadian government's use of military force to suppress the anti-conscription Easter Riots that occurred in Quebec City between 28 March and 1 April 1918. The riots demonstrated French-Canadian dissatisfaction with the national war effort and the introduction of conscription, and exacerbated nationwide fears that a state of rebellion existed in the French-speaking province of Quebec. The Canadian government's reaction was immediate and firm; martial law was proclaimed, habeas corpus was suspended, and over six thousand English-speaking soldiers were deployed to Quebec during and after the riots to maintain order and enforce conscription, the last of these troops leaving the province in early 1919. The Easter Riots were extremely violent, causing important destruction of property and over 150 civilian and military casualties, including at least four dead when soldiers opened fire on rioters. This article will demonstrate the extent to which the Canadian government apprehended insurrection in Quebec during the First World War and how determined it was under difficult wartime conditions to prevent the rise of a major national crisis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".