Cabin, Quarter, Plantation: Architecture and Landscapes of North American Slavery
Bibliographic record
Abstract
The built environment of North America cannot be fully understood without taking slavery into account, argue the architectural and landscape historians Clifton Ellis and Rebecca Ginsburg in their edited volume Cabin, Quarter, Plantation. This excellent collection of twelve scholarly essays reveals the impact of the institution of chattel bondage on the built landscape, a term that refers to not only buildings but also to “yards, streets, fields, alleys, obscure trails, dusty lanes, fences, tree lines and all other elements of our surroundings that are the product of human intervention” (p. 2). Drawing from seven original and five reprinted studies from various disciplines, the editors have produced a fine collection that represents “scholars' best understandings to date of the interplay between slavery and the design, construction, and use of North America's built environment” (p. 9). Central to the essays are three interrelated theoretical concepts. The first is slave agency. Several of the studies chosen for this collection illuminate the ways bondspeople appropriated or actively manipulated space and the material world in response to slavery. Garrett Fesler's essay, for example, illustrates how the “swept yard” in front of slaves' houses reveals mechanisms of cultural survival that allowed Africans to apply traditional notions of outdoor communal spaces to the plantation setting (pp. 32–33). Barbara Heath's essay on the use of space on Virginia plantations similarly analyzes the existence of subfloor pits in slaves' houses, used to hide prohibited wares.
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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 | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 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".