Julian Barnes’s "England, England" as a condition of England novel
Bibliographic record
Abstract
Condition of England novels are born out of the acknowledge ment ofas Steven Connor put it -"the potential of the novel to imagine, project and preserve forms of national and collective identity."The task to represent England and Englishness is usu ally undertaken in what is perceived to be a time of political, eco nomic and cultural transformations.In his outline of this fictional tradition Connor points out that this potential is best actualised in realist fiction, where "realist" is taken to mean the opposite of "experimental."He traces the origin of the phenomenon to the Victorian novel which responded to the imperative to diagnose the condition of the country and society.Referring to D.H. Lawrence's fiction to challenge the widely held belief that modernism recoiled from the public perspective in fiction, Connor nevertheless largely concedes that it was only the post-Second-World-War novel that consciously resumed the nineteenth-century aspiration to analyse and display in fiction the condition of England.1 Margaret Drabble's novels correspond to the writer's well-known identification with the realist tradition as well as her ambition to provide a fictional portrayal of England and Englishness.Angus Wilson's
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".