Bibliographic record
Abstract
The Crimean War (1854–6) was, in the words of Eric Hobsbawn (2010), ‘the nearest thing to a general European war between 1815 and 1914’. Whereas it figures large in the national mythologies of Britain and Russia, in France it remains very much a footnote. This is despite the fact that it is the only nineteenth-century war the French ultimately won. But in the view of many, to quote Jules Michelet (1857), ‘La conquête du lama est dix fois plus importante que la conquête de Crimée.’ It would seem that the Crimean War has no place in the canon of culturally retained historical events that define modern French identity. Though news of the war in the contemporary press and popular literature was ubiquitous, it does not figure in the canonical literature of time. This paper considers how the Crimean War was and was not represented in French literature in the second half of the nineteenth-century.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".