Bibliographic record
Abstract
After the conclusion of Pontiac's Uprising, frontier trade reopened in 1765. Unfortunately, for the colonists, the renewed activity favored the French in Canada and Illinois and the British traders in Quebec and Montreal. Only three British regiments were assigned to frontier duty, an inadequate number of troops to enforce trade regulations against the French. To keep the peace with local tribes, the British army allowed the French to trade anywhere, while colonial merchants were restricted to army trading posts. Had the army been more astute in protecting colonial interests, colonial merchants might have been more favorable toward paying taxes in support of military efforts. Frontier commerce was a major component of the colonial economy, ranking third in export behind tobacco and rice. The European demand for fashionable broad-brimmed beaver hats was the driving force that created turmoil on the frontier from 1765 to 1768. After the cession of Canada to Britain in 1763, the French obtained half the beaver pelt exports by forcibly diverting them from Quebec to New Orleans and then on to France. This competition hurt wealthy colonial merchants in New York City and Philadelphia, who blamed the British army and set the tone for the coming conflict.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.107 | 0.016 |
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".