"The Nest of Tories which has Invested this Precinct": The Loyalists of Newburgh, New York
Bibliographic record
Abstract
This thesis uses a case study approach to examine loyalism during the American Revolution, by considering the Loyalists of Newburgh, New York. I examine the Loyalist community by exploring its origins before the Revolution, analyzing its composition, examining the Loyalists' wartime experiences, and by considering their post-war exile. Studying Newburgh's Loyalists allows for a nuanced understanding of loyalism both in the Hudson Valley and more generally. I argue that migration, religion, wealth, and geographic location shaped Loyalist communities and their experiences. My thesis is divided into four chapters, the first of which considers the origins of the Loyalist community, which dates to religious conflict in the town during the 1750s and 1760s. Anglicans fought with dissenting Protestants over control of the church glebe, creating a division which split the community along religious lines when the American Revolutionary War began. Anglicans often became Loyalists, while the Presbyterian-led dissenters were almost entirely Patriots. In the second chapter, I examine the size and composition of the Loyalists from Newburgh. The Loyalist population of Newburgh was smaller than average in New York, but was much larger than any Loyalist community in its area. Men loyal to the King were generally Anglican, poorer than their Revolutionary counterparts, and were often related to one another. My third chapter explores the war experiences of the Loyalists, both in Newburgh and behind British lines. In Newburgh, men loyal to the King faced increasing persecution as war progressed, which intensified when there was a military threat from British forces. Persecution peaked in 1777, when the Hudson Valley faced British invasion from New York City to its south as well as from Canada in the north. Patriots in Newburgh were vigilant in rooting out Loyalist dissidents as Newburgh's sizeable Loyalist population was a military liability in case of attack. As a result of their maltreatment, many Loyalists fled to British-occupied New York City. They often joined Loyalist provincial units where they were frequently used as guides and recruiters in the countryside because they had knowledge of the area. My final chapter considers the post-war exile of Newburgh's Loyalists in Canada. Most settled in what became New Brunswick where they tried to recreate aspects of their old society by settling near former neighbors, and continuing to adhere to the Anglican Church. Many of the Loyalists, who had been poor in Newburgh, improved their social status and gained wealth in their new society. This thesis fills a historiographical gap on the subject of loyalism in the Hudson Valley, and also demonstrates the influence of migration, religion, wealth, and geographic location on Loyalist communities and the experiences of individual Loyalists.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".