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Record W7001057930

The Impact of the Saratoga Campaign of 1777 Upon the Communities of Upstate New York During the American Revolution

2022· dissertation· en· W7001057930 on OpenAlexaboutno aff

Bibliographic record

VenueCUNY Academic Works (City University of New York) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHeadlineGeorge (robot)Government (linguistics)CeylonGloomCircumstantial evidence
DOInot available

Abstract

fetched live from OpenAlex

From the spring of 1776 to the summer of 1777, there was a looming threat to the northern region of the colony of New York bordering Canada. Across the border, British forces were marshaling for an invasion. Finally, in June of 1777, the inevitable came true; British General John Burgoyne moved south from St. John’s toward Lake Champlain in upstate New York with an army numbering approximately 9,500. This diverse force consisted of British army regulars, hired German troops, Indian allies, Canadian volunteers and loyalists, and a glut of camp followers, who helped support Burgoyne’s army. His aim was to move south to the city of Albany to link up with two other British armies approaching from the west and the south. These advances were intended to gain British tactical control over the Hudson River Valley, thereby separating the New England colonies (which the British saw as the spark of the rebellion) from the rest of the American colonies. The plan was known as “The Grand Strategy”, and it had been approved by the British High Command towards the end of the previous year as the overriding strategy for the 1777 campaign season. The “Grand Strategy”, however, was flawed from its inception. Resistance to the British advances by Patriot forces and militias, aided by local communities, was completely underestimated by the British. This flaw was exacerbated by the forbidding terrain of upstate New York, as well as a complete failure of coordination between Burgoyne’s advance from the north, Colonel Barry St. Leger’s advance from the west, and General William Howe’s forces positioned to the south in New York City.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.672

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.006
Scholarly communication0.0070.002
Open science0.0010.007
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0200.002

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.

Opus teacher head0.025
GPT teacher head0.261
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCUNY Academic Works (City University of New York)Same topicCanadian Identity and HistoryFrench-language works237,207