“A Mixed Assemblage of Persons”: Race and Tavern Space in Upper Canada
Bibliographic record
Abstract
This tavern story about an 1832 Saturday night on the town in Brantford, Upper Canada, addresses the complexities of racialized relations in “public places” generally and the tavern’s bar room in particular. It juxtaposes tavern-goers who engaged in “heterogenous” sociability with the “‘high pressure’ prejudice” of a “‘Yankee’” barkeeper. It challenges us to understand what such moments of multiracial public life meant in a society permeated by racialized thought and practice. There was a strange contradiction between White settlers’ marginalization of Black and First Nations peoples and the sometimes easy accommodation afforded them in the public houses. Although accommodation to people of colour was also illegally, and sometimes violently, denied, tavern stories complicate historical interpretations focusing on conflict. Without questioning these analyses, or the evidence supporting them, the stories suggest that something more subtle was also going on. They invite serious attention to the colony’s many taverns as sites where people chose to relax racial boundaries as often as they chose to enforce them. Maybe it was just the whiskey and the wine; without comparable work on other public spaces, the typicality of a tavern-based history will remain an open question. But because “Indians” as well as the “blacks and whites” all went there, the taverns show how race, as one socially constructed category, shaped ordinary, everyday human interactions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.089 | 0.024 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".