Bibliographic record
Abstract
Opening New Markets by the retired museum director Walter S. Dunn Jr. is his third offering in a series describing the British army and the American frontier in the years preceding the American Revolution. This volume is a sequel to Frontier Profit and Loss: The British Army and the Fur Traders, 1760–1764, published in 1998, and The New Imperial Economy: The British Army and the New American Frontier, 1764–1768, published in 2001. In Opening New Markets, Dunn argues that the economic consequences of British policies along the trans-Appalachian frontier in the wake of the Seven Years' War benefited British merchants and French traders in Canada while harming the interests of American merchants. The detrimental effects of British policy could be seen in two aspects of the frontier economy. First, American merchants doing business in Canada, the lower Great Lakes region, Pennsylvania, the Ohio Valley, and the Mississippi Valley had prospered during the war by supplying the British army while it served in the conflict. But after 1768 these same merchants saw their incomes diminish drastically as the British both reduced the number of troops in North America and redeployed many regiments stationed along the western border to the East Coast.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.148 | 0.069 |
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".