The French, English and a Fish: How They Transformed the Island of Newfoundland, 1696-1713
Bibliographic record
Abstract
abstract: Newfoundland is an island on the east coast of Canada that is mostly forgotten to the study of history. This paper looks in depth at the fighting between France and England between 1696 and 1713, which in Europe coincided with the Nine Years’ War and the War of the Spanish Succession. In 1696, fighting broke out on Newfoundland between England and France because of the Nine Years’ War. Pierre le Moyne d’Iberville, a French officer, commanded the attacks on over twenty English settlements. The attacks lasted less than a year. Attacks would happen again because of the War of the Spanish Succession. France and England would attack each other trying to gain control of the prized commodity of the island, the cod fish. This study looks at how French and English fighting on Newfoundland helped to change the landscape and shaped the way the history of the French and English on the island is portrayed today. Historians tend to look more at the modern history of the island such as: soldiers in World War I and World War II, when Newfoundland became a Canadian province, and the English history of the island. This study argues that, by studying French and English fighting on the island, we can better see the historical significance of Newfoundland.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".