Fannin’ Flies and Tellin’ Lies: Black Runaways and American Tales of Life in British Canada before the Civil War
Bibliographic record
Abstract
Fannin’ Flies and Tellin’ Lies examines the many falsehoods told by slaveholders in the American South to prevent enslaved Blacks from running away to British Canada throughout the antebellum. Blacks were wrongly instructed on Canada including fabrications ranging from the Monarch would demand half of their earnings to rice was the only crop that could be grown in the British colony. At times the lies were totally inaccurate and humorous; on occasion they were half-truths or white lies, but indefinitely these falsehoods, instead of misinforming Blacks, suggested to them the benefits of Canada. Blacks deconstructed and reacted to lies by concealing their desire to defile the institution of slavery by flight to Canada and turned the art of lying into a tool of insurrection and a means of greater liberation.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.031 | 0.028 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".