Maine’s Mode of Privateering: A Tale of Fraud and Collusion in the Northeast Borderlands, 1812–1815
Bibliographic record
Abstract
The American declaration of war passed by Congress in June 1812 was followed by a prize act which authorised the issuing of Letters of marque. These commissions or licenses allowed American citizens to fit out privately armed vessels to seize British ships. Although most privateers complied with Congress’s instructions, their counterparts operating along the Maine coast used their commissions to further own economic self-interest by orchestrating pre-arranged captures with British merchants in Nova Scotia and New Brunswick. Since the British government encouraged its subjects to trade with the enemy to undermine the American war effort, American privateers assumed most of the risks. Merchants and mariners from as far away as New York and Connecticut traveled to Maine to trade with the British despite the hazards of detection. As these privateers engaged in fraud, other Americans turned to vigilante violence to uncover and foil these schemes. After the British occupied Eastern Maine in the summer of 1814 trading with the enemy became illegal on the British side of the border. Despite the risks, British merchants continued to engage in trade with the enemy. Ultimately, persistence of conflict and accommodation in the Northeastern Borderlands, the area comprising Maine, Nova Scotia and New Brunswick, helped undermined Eastern Maine’s allegiance to the United States.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.018 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".