Bibliographic record
Abstract
The family tree Before going on to examine more directly the themes and techniques of L'Assommoir , we still need to relate the novel to Zola's naturalist aesthetics and to the second aspect of the scheme of the Rougon-Macquart series: the natural history of a family under the Second Empire. Without the class qualifier, Zola's definition of the subject of L'Assommoir in his preface to the novel, ‘the fatal decline of a working-class family’, could apply more generally to the whole of the Rougon-Macquart saga. The ‘fatal’ element is, as we have seen, largely sociohistorical, but it is also, more appropriately, biological, invested in the laws of heredity as Zola and many of his contemporaries understood them: a fatal, disruptive force. There are very few happy combinations of genes, or, in terms more appropriate to Zola's age, few happy mixings of traits and dispositions in the Rougon-Macquart . Zola was drawn as much to the dramatic possibilities offered by the laws of heredity as to their scientific validity. They also provided the novelist with a framework and a further unifying theme for his series. The early plans for the series contain detailed notes on Zola's main scientific source: an imposing study by Dr Prosper Lucas, dating from 1847–50, his Traité de l'hérédité naturelle ( Treatise on Natural Heredity ), in its short title. Zola would later update his information with some more recent theories when, in 1892, he came to write the final volume of the series, Le Docteur Pascal (1893), where the whole history of the family is recapitulated.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".