Slavery in the City: Architecture and Landscapes of Urban Slavery in North America
Bibliographic record
Abstract
Although most studies of built environments and American slavery have focused on rural plantations, the investigations in Slavery in the City deal with particular towns and cities in which slaveholders and their bondsmen coexisted in urban settings. Without the supervision they would have had in the field, blacks instead roamed city streets on errands for their masters, engaged in outside work, and lived in close proximity to freed blacks, challenging white power and requiring a range of solutions to keep the enslaved subjugated. These essays—grounded in architectural and archeological research—present a spectrum of settings. Edward A. Chappell's analysis of domestic architecture focuses on prerevolutionary Williamsburg, later on Annapolis, and still later on Falmouth, a prosperous center of the sugar trade in Jamaica. John Michael Vlach's investigation deals with the North, where, despite some thirty thousand slaves listed in official records for New York and New Jersey alone, few examples of their housing survive. Clifton Ellis's analysis of Annapolis pools information from tax and census lists with lot histories and maps, and also uses local records to describe a relatively stable mixed community. Gina Haney's research is centered on Charleston, and Kenneth Hafertepe explores housing and slavery as it expanded westward into Texas, where lots were more expansive and less enclosed (one chapter illustration shows a slave quarter on a back lot that was surrounded by nothing more than a picket fence in Houston). Charles H. Faulkner focuses on Knoxville, Tennessee, an urban center for the region with important trade ties to areas farther south. And Lisa Tolbert uses court records of a murder trial, giving us a snapshot of a community of bondsmen and their interaction with white power in a small town in Tennessee.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".