A Not-So-New World: Empire and Environment in French Colonial North America
Bibliographic record
Abstract
Christopher Parsons’ important new monograph demonstrates that the prominent Enlightenment-era debates regarding global human and biological diversity originated from the colonial experience of European nations during the seventeenth century and the resulting conflict over the means of knowledge production related to the New World. Taking the French experience in what is now the St. Lawrence River valley between modern Québec and Montréal as his test case, Parsons offers a compelling demonstration of how French attitudes towards the Canadian environment changed from the early-seventeenth-century period of exploration and initial settlement to the British conquest of 1760. Undergirded by impressive research in primary sources, Parsons’ interpretation shows how insights from environmental history and the history of science permit a significant reconsideration of French North American settler colonialism. The key change traced by Parsons is the decreasing confidence over time of French colonial projectors in their ability to transform, through a rehabilitative process of cultivation, the North American environment into a replica of France. Extended etymological discussions of French usage of the descriptive term sauvage helps the reader to appreciate the ways in which early colonizers such as Samuel de Champlain represented Canada as an essentially familiar place that could, and would, with deliberate effort, be made to resemble France. In other words, Parsons contends that while French explorers, missionaries and colonists initially understood Canada as a ‘not-so-new’ place, by the middle of the eighteenth-century long experience of the resident French population with its environment (particularly the harsh winters) engendered widespread agreement regarding the ‘novelty’ of its flora and climate on both sides of the Atlantic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".