Mr. De la Barre’s Expedition, and some Remarkable Transactions in 1684.
Bibliographic record
Abstract
In the time of peace between the French and the Five Nations, the French built their fort at Teiodondoraghi or Missilimakinak, and made a settlement there. The French took all the precautions in their power, not only to restrain the Indians by force, but also to gain their affections by sending missionaries among them. The only obstacle they met was from the Five Nations, who introduced the English of New-York into the Lakes to trade with the Indians that lived around them. This made the French uneasy because they saw the English as dangerous rivals. The Sennekas lived next to the Lakes, and nearest to the Nations with whom the French traded. They were so averse to the French that they allied themselves with the English. This chapter details events following Mr. De la Barre's (the Governor of Canada) message to Coll. Dongan, citing the need to bring the Five Nations to reason by force.
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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 | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.042 | 0.010 |
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".