Bibliographic record
Abstract
In his journalism and novels (particularly Bleak House and Our Mutual Friend ), Charles Dickens presents London as a writer’s necropolis, a city of disintegrating paper and dead letters, a failed archival space. This essay examines a nexus of images in Dickens’ work – involving dust, Egyptian ruins and mummies, and paper – as revealing characteristic Victorian concerns regarding the changing status of paper and the archive. With reference to developments in papermaking technologies and the beginnings of Egyptian archaeology, I demonstrate some of the ways that nineteenth-century authors were newly troubled by the archival as such. Dickens is particularly haunted by an urban vision of paper as everywhere and everywhere turning into blank, wasting forms. I connect this phenomenon to the British reception of the material legacies of ancient Egypt, particularly the mummified dead. The Victorian era was the great age of paper, as technological developments transformed the industry and multiplied its productivity many times over. Read in the context of these changes, and in relation to Egyptology (that other burgeoning industry of records and remains), the work of Dickens reflects deep anxieties regarding the whelming flood of precariously fragile paper—anxieties that have a center in the necropolitan library.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.040 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".