Marshalling Memory: A Historiographical Biography of Ernest Alexander Cruikshank
Bibliographic record
Abstract
E.A. Cruikshank was one of Canada’s most influential and respected historians of the late nineteenth and early twentieth centuries. As chairman of Canada’s Historic Sites and Monuments Board for 20 years, he played a central role in constructing Canadian historical memory. In this sense, Cruikshank’s historical works reveal the mutual interplay of historical research and public memory in framing national sentiment; yet, although he had a national reputation, Cruikshank was primarily a local historian who translated local Niagara sentiments into a national history, principally through his interest in the War of 1812. Traces of his influence can still be seen. What is most striking, though, is that sympathy for Cruikshank’s vision has persisted even into this century, as the messages surrounding Canada’s official commemoration of the War of 1812’s bicentennial suggest. Thus his works continue to be instructive for understanding how history and memory reinforce one another.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".