Conrad Eymann: A Microhistory of Changing German-Canadian Identity during the First World War
Bibliographic record
Abstract
How did the turbulent years of the First World War and the violently anti-German sentiments that developed during that time influence and change German-Canadian identity?While Canada was at war in Europe with Germany and her allies from 1914 to 1918, the treatment of domestic German immigrants deteriorated in some cases to the point of public hostility by native-Canadians.The reactions to this crisis by the Germanborn immigrant and Editor-in-chief Conrad Eymann of the German-language newspaper Der Courier from Regina, Saskatchewan, can offer valuable insight into the lives and culture of German-Canadians during these years.Eymann's correspondence with the Chief Press Censor Ernest Chambers, Police Commissioner A.B. Perry, and Prime Minister Sir Robert Borden -as well as Eymann's file recorded by the Royal North-West Mounted Police and the articles he published in Der Courier -are among the more valuable primary sources examined in this work.In this thesis, I analyze these sources and others through a microhistorical approach in an effort to develop an understanding of German-Canadian identity that both complements and challenges the accepted grand narrative view of Canadian history.That is, the research and discoveries presented in this thesis is hoped to both complement and challenge the widely accepted grand narrative perceptions of identity development during the First World War.iv This work is dedicated to Evelyn
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.034 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".