Bibliographic record
Abstract
The 700-year history of the novel in English defies straightforward telling. Geographically and culturally boundless, with contributions from Great Britain, Ireland, America, Canada, Australia, India, the Caribbean, and Southern Africa; influenced by great novelists working in other languages; and encompassing a range of genres, the story of the novel in English unfolds like a richly varied landscape that invites exploration rather than a linear journey. In The Novel: A Biography, Michael Schmidt does full justice to its complexity.Like his hero Ford Madox Ford in The March of Literature, Schmidt chooses as his traveling companions not critics or theorists but artist practitioners, men and women who feel hot love for the books they admire, and fulminate against those they dislike. It is their insights Schmidt cares about. Quoting from the letters, diaries, reviews, and essays of novelists and drawing on their biographies, Schmidt invites us into the creative dialogues between authors and between books, and suggests how these dialogues have shaped the development of the novel in English.Schmidt believes there is something fundamentally subversive about art: he portrays the novel as a liberalizing force and a revolutionary stimulus. But whatever purpose the novel serves in a given era, a work endures not because of its subject, themes, political stance, or social aims but because of its language, its sheer invention, and its resistance to cliche--some irreducible quality that keeps readers coming back to its pages.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".