Bibliographic record
Abstract
In the labyrinth Whereas French critics have been more inclined to study the character ‘system’ in the novel, critics writing in the English tradition, faithful to a long-standing assumption that the hallmark of great novel writing is the creation of characters, have emphasised the ‘roundness’ of Gervaise's character, the uniqueness of Zola's humble protagonist. Angus Wilson, for example, has described her as ‘perhaps the most completely conceived character, belonging to that great class of submerged, unindividual figures that make up the very poor, to be found in all nineteenth-century fiction’ ( Emile Zola , p. 122). ‘Neither good nor bad’, ‘in short, very likeable’ (‘sympathique’), are the terms with which Zola described his character in his preliminary notes. ‘Gervaise is the most likeable and the most tender of the figures that I have yet created,’ he wrote in his letter to Le Bien public (15 February 1877); ‘she remains good to the very end.’ L'Assommoir clearly conforms to the biographical tradition of the novel, as its first titles suggested, to the type of novel that traces the fortunes and misfortunes of a protagonist and engages the sympathy of readers, who see reflected in the character's failings the foibles of humanity, and sometimes their own. But Zola, with his characteristic sense of order, also instructed himself in his chapter plans: ‘Divide my characters into good and bad.’
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".