"A Beauty in the Kitchen": The Introduction of the Cookstove as a Mechanism of Change in Charleston's Historic Kitchens
Bibliographic record
Abstract
While Charleston’s historic houses have long captivated visitors, scholars, and preservationists, the architecture of these properties’ kitchens and the ways people cooked in these historic spaces have long been overlooked, in part because their historic fabric has often been obscured by later alterations or demolition. While interpretation of these historic spaces in certain house museums, such as the Nathaniel Russell House or Heyward-Washington House, now include information on the lives of the enslaved who cooked in these kitchens, the understanding of cooking technology, specifically the transition from hearth cooking to cooking on cookstoves, in Charleston remains largely unstudied. In the latter half of the nineteenth century, the manner in which Charlestonians prepared their meals underwent a significant transition with the adoption of the cookstove. This technology proved to be a cleaner, more efficient, and more affordable means of cooking and baking food. Scholarly literature has focused primarily on this technological introduction and dissemination in northern states. This narrative remains little studied in the South where slavery is hypothesized to have slowed its adoption. This thesis aims to document Charleston’s transition from hearth cooking to cookstove technology through period newspaper advertisements, supplemented by an inventory of several Charleston properties and the probable means of cooking at their time of construction.\nThese advertisements and field investigations locate the widespread adoption and use of cookstove technology in the last quarter of the nineteenth century in Charleston, specifically between 1875 and 1885. This process gradually displaced traditional hearth cooking that had been the work of enslaved men and women for so many generations until the disruptions of the Civil War and Reconstruction. This research underscores the need for further study into this daily activity essential to the lives of all of Charleston’s residents and how they prepared their food.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".