Britain's 1814 Occupation of Pensecola and America's Response: An Episode of the War of 1812 in the Southeastern Borderlands
Bibliographic record
Abstract
With the appointment of Alexander Cochrane to Commander of the North American Squadron in the summer of 1814, Britain began to formalize a strategy that called for a systematic series of campaigns against the Chesapeake, New England, South Carolina, Georgia, and New Orleans with the ultimate aim of bringing the United States to its knees while protecting Canada. The bulk of the attack on New Orleans was to be carried out in a straight-forward assault by the Royal Navy, but forces were to come from a number of directions. In the build-up to the attack, it was envisioned that some of these armies would launch raids across the Deep South at strategically important locations designed to distract American forces. Over the course of 1814 and into 1815, Colonel Edward Nicolls of the Royal Marines, and George Woodbine, a white trader from Jamaica, were put in charge of raising one of these forces from the slave and Indian populations of the Southeastern borderlands. Nicolls and Woodbine erected a fort on the Apalachicola River in West Florida and between August and November of 1814, occupied the capital of Spanish West Florida, Pensacola.This study examines Nicolls's and Woodbine's efforts to raise a multi-racial army from their Pensacola base and considers the extent to which the Southeast's unique conditions shaped their efforts as well as America's response.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".