Mary Elizabeth Braddon in Paris: The Cross-Chunnel Relations of Periodical Sensational Literature in the 1870s–1880s
Bibliographic record
Abstract
T he setting: “the quietest road” in the Marais quarter in Paris— rue St Gilles, “where gossip flourishes as rankly as the grass between the paving-stones.” The time: a Saturday evening, April 27, 1872. A man of thirty is noticed in the area as he wanders from door to door seeking information about the house of M. Vincent Favoral, supposedly for a cousin of his who is considering a job offer as a cook in the mansion of M. Favoral, at number 38 of rue St Gilles, “an old type of house, not so common anymore, that the housing market values at 1200 francs per square meter.” M. Favoral is chief cashier and one of the principal shareholders at Mutual Credit Bank, an institution that, “sprung up with the Second Empire, won heavily on the bourse the day the Coup d’État was played on the street.” While he sits at dinner entertaining his guests for the evening, he is interrupted by M. de Thaller, an elegant baron, who takes him to another room for an animated conversation. All money in the bank is lost, the police wait outside of the house to arrest him for forgery and embezzlement. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.018 | 0.021 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".