Bibliographic record
Abstract
It is a vast generalization to say that all Federalists were anti-war, and that Federalist, anti-war feeling was centered in the Puritan northeast. It is equally an oversimplification to assume that all westerners and southerners were pro-war Republicans. But these assumptions were just as common at the time as they are today. The war of 1812, although not one of the most significant wars in the nation’s history, is one of the most complex. Over the years, dozen of causes have been suggested for the conflict: American merchants’ profits from the war in Europe, westerners’ attempt to further expand the country’s borders, or even a Napoleonic conspiracy against Britain. The simplified explanation is this: Despite avowed neutrality in the war between Britain and France, the United States was steadily being drawn into the conflict. American merchant ships traded with both countries and thus became the target of both the British and French navies. The British navy, suffering from a high desertion rate and desperate for sailors, began seizing American merchant ships and impressing American seamen to fill their ranks. A series of skirmishes with the British-backed Shawnee along the Canadian border solidified President James Madison’s conviction that open conflict was necessary, and Congress declared war on Britain on June 18, 1812.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.026 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".