Bibliographic record
Abstract
This article examines the current campaign to eliminate the name of Dundas from the streets of Toronto. Derivative of the controversy in Edinburgh, a petition was mustered in 2020 to remove Henry Dundas’ name, on the principal ground that this premier Scottish politician delayed the abolition of the slave trade by fifteen years and sent half a million slaves into slavery. The article highlights the fallacies of this claim, the limitations of the historical evidence behind it, and the questionable way in which it was pushed through Toronto city council. The Dundas episode illustrates a disturbing trend in historical reckonings in which everything is judged by anachronistic standards of contemporary social justice. Henry Dundas was a man of the enlightenment and a man of empire, who was in power during decades of revolutionary upheaval and black rebellion. His differences with other abolitionists were essentially about the means, not ends – admitting the injustice of the slave trade and slavery but unwilling to risk a transition to emancipation without safeguarding British imperial and capitalist interests. In this respect, Dundas represented the mainstream of British parliamentary opinion. Quite apart from the logistical difficulties of pursuing abolition in time of imperial war, Dundas cannot be scapegoated for singlehandedly sending thousands of Africans into slavery. Indeed, his pragmatic approach to abolition ultimately proved the way forward.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.002 |
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.
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".