“Thanks be to God that I am Elected to Canada”: The Formulation of the Black Canadian Jeremiad, 1830-61
Bibliographic record
Abstract
This essay identifies the Black Canadian jeremiad, 1830-61, which grew and flourished from the African-American jeremiad and its polemics. A study of this importance places the jeremiad within the context of Black Canadian protest. To deliver their jeremiads to Canadian audiences and seek aid in the deconstruction of American and Canadian racial prejudice, Black Canadian Jeremiahs used various means and associations, and utilized the rhetoric of the jeremiad to demonstrate Black devotion to self-determination. They also employed the jeremiad to contest pro-slavery ideas in both the United States and Canada. The rhetoric of the Black Canadian jeremiad was situated, then, in the context of two evolving debates: 1) American slavery and 2) Canadian prejudice.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.058 | 0.027 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".