The ‘wilds of Brompton’: Mapping Nineteenth-Century Women Writers’ Early Careers in the Sociable London Suburbs
Bibliographic record
Abstract
ABSTRACT In this paper, we geocode the residences of nineteenth-century Brompton residents to the level of the building in order to argue that literary sociability and propinquity – leading to face-to-face interaction with writers, editors, artists, actors, and publishers – may have played a more important role in the formation of women’s literary careers than scholars have yet recognized. Taking the popular novelist and poet Dinah Craik as our case study, we argue that the walkability as well as the informal and inexpensive literary sociability of the area made Brompton a fertile ground for the early careers of nineteenth-century women writers. Following Alan Liu’s work in Critical Infrastructure studies, we attempt through mapping to reanimate connections that have been lost to time, establishing the importance of Brompton as a literary, artistic, and intellectual neighbourhood in the nineteenth century, and of propinquity in supporting the careers of women writers. Expanding on Sarah Bilston’s recent work on the suburbs as fertile grounds for the careers of Victorian women writers, we add a spatial dimension to Robert Darnton’s well-known print network, placing the private home, a site of literary sociability, as a central node in public print networks.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".