Navigating wilderness and borderland: the Arnold expedition from Maine to Quebec, 1775
Bibliographic record
Abstract
There has not been a published work of academic history focused on Benedict Arnold's expedition through Maine, during the invasion of Canada in 1775, since Justin Smith authored Arnold's March from Cambridge to Quebec in 1903. Upon reading the diaries kept by Arnold and over one dozen other soldiers on their march to Quebec, the need for a reexamination of this historical topic through the lenses of environmental history and borderlands history became apparent. The expedition began by facing the task of navigating a threatening and unfamiliar wilderness. Through the imposition of order on the inchoate landscape of Maine the expedition was able to make the wilderness less threatening and more useful. There was also an immense sense of awe and reverence for this new and unique natural landscape. Once properly understood and made predictable, the wilds of Maine provided not only food, medicine, and supplies for the expedition, but also visual aesthetics - the picturesque beauty of the environment and the wonders of the natural world - which nourished the troops' bodies and minds. As the expedition transitioned from navigating the wilderness to navigating the borderlands they were faced with another unknown threat - the population of the Beauce region of Quebec. There were many social and cultural obstacles that had to be negotiated, including language, religion, race, loyalty, and most importantly the divide between soldier and citizen. Much like the wilderness, however, the borderlands, once properly understood became a source of support and accommodation. Though letters from political leaders, military strategist, and translators helped to bridge the social and cultural divides, the major impetus of accommodation was the wilds of Maine. The state of suffering inflicted by the wilderness allowed Arnold's force to be viewed by the Canadien and Wabanaki populace of the Beauce region not as an invading force, but instead as a band of courageous individuals in a condition of need. At the same time, the need for provisions and rest was so debilitating that the revolutionary force was not able to overpower or coerce their hosts. The aid provided by the habitants created a bond beyond the immediate material level that led to social and interpersonal relationships. This study illustrates the ability of the natural environment to shape the course of human events.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".