"Le Canada est un païs de bois" : forest resources and shipbuilding in New France, 1660-1760
Bibliographic record
Abstract
The colonial contribution to the French naval shipbuilding industry in the seventeenth and eighteenth centuries, explored within the context of the forest from which the resources for the industry were taken, was a remarkably successful venture that came to an end with the onset of war. In the past, the end of the French naval shipbuilding industry in New France has been attributed to the action or inaction of France that resulted in the inefficient use of forest resources. Issues of interest in, organization or support of colonial efforts by France, however, were nevertheless, limited by the immutable realities of the colonial forest environment. This thesis argues that the success of the industry, considered within the appropriate context, is a consequence of colonial persistence in the face of constraints imposed by the colonial forest environment---despite these other significant issues. The official correspondence, written by colonial officials in New France, record colonial efforts to supply France with timber and detail the development of a naval shipbuilding industry in the colony. These documents provide source material for a case study that demonstrates the constraints imposed by the colonial forests on the experience of colonists, timber suppliers and shipbuilders. The colonial forest was not the same as the forests in France. A simple transfer of knowledge and practice from one forest to another was insufficient to deal with the differences in climate, forest age, tree species and the extent to which human activity affected the different forests. These differences challenged the way in which colonists could use forest resources for their own needs, for export to France and for naval construction. To consider this use of resources, without considering the differences between the available materials in the colony and those available in France, is to look at the story removed from the setting in which it took place. The unique forest in the colony was the setting in which colonial shipbuilding took place. Any study of the development of this industry, or any other industry that relied on forest resources, must give consideration to the constraints and realities of that forest.
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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 | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".