Following Fortune: the story of the Nova Scotia Black Loyalists
Bibliographic record
Abstract
abstract: About one in ten refugees from the American Revolution was African-descended, and unlike many white Loyalists fleeing war in the thirteen mainland North American colonies, black Loyalists were people without a country. Most were fleeing slavery in Virginia or the Carolinas, yet not fully able to claim to be British subjects, despite many heeding the call to join British forces. Among the 40,000 Loyalists who departed, around 3,500 black Loyalists evacuated from the newly founded United States between the years of 1776 and 1785. I hope to evaluate the movement patterns and thought process behind this particular group with what choices they ultimately had after the war using Dunmore’s Proclamation as a means to freedom. These black Loyalists faced the difficult decision in choosing what identity they would side with once they left. These former slaves ultimately had to choose between becoming forced migrants with the losing side of the war or staying with the winning side of the war as people bound by chains. Although there were a multitude of fascinating tales that could be told through the lens of these black Loyalists, one particular family caught my eye within my research. This story is the journey of the Fortune family who chose to run away from American slavery to migrate to Nova Scotia. Their story will grant me access to analyze the extreme discrimination families met as they fled, the contempt the new colonies felt against them, as well as the evolution of their societal roles as some of these immigrants integrated into their new country and became accepted as respected individuals. Furthermore, their tale aided me in understanding what caused some emigrant black Loyalists to stay in Nova Scotia despite the hardships they faced as outsiders who were unwelcome from the perspective of native white Nova Scotians.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.045 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".