Christian Ayne Crouch.<i>Nobility Lost: French and Canadian Martial Cultures, Indians, and the End of New France</i>.
Bibliographic record
Abstract
This excellent book examines both the defeat of New France during the Seven Years’ War and the impact of the military disaster on French imperialism. Christian Ayne Crouch views the conquest through the lens of the “culture war” (15) between French and Canadian officers over the rules governing warfare. While Canadians accepted the need to engage in diplomacy and warfare on Native terms, French elites demanded Native subjugation and rejected indigenous martial practices. Versailles, by siding with the French troops over the Canadians, sealed the colony’s fate. Furthermore, France’s rethinking of empire in the wake of defeat virtually erased New France from the national memory, while producing a new imperial model whose ideological legacy would linger for two centuries. Four chapters focus on “the encounter between the Canadian, Indian, and French cultures of war” (4) during the final struggle for New France. Canadian martial culture emerged in the 1680s, with the arrival from France of compagnies franches de la marine and the massive mobilization of Canadian militiamen to counter the Iroquois. The compagnies franches were colonial troops serving under the auspices of the naval ministry. Canadian nobles soon dominated the officer corps, enabling them to express their military ethos while enriching themselves through the Indian trade.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".