Bibliographic record
Abstract
1. S. T. Coleridge, The Statesman’s Manual: A Lay Sermon, quoted in Paul Keen, ed., Revolutions in Romantic Literature: An Anthology of Print Culture, 1780–1832 (Peterborough, Ontario, 2004), 19. 2. S. T. Coleridge, Biographia Literaria, ed. James Engell and W. Jackson Bate (Princeton, N.J., 1983), 48–49. 3. Percy Shelley, The Major Works (Oxford, 2003), 680. To be sure, there were those with opposing views: Anna Barbauld, who in her 1810 anthology British Novelists noted that while the “humble novel” might be “condemned by the grave, and despised by the fastidious, . . . their leaves are seldom found unopened” ( “On the Origin and Profess of Novel-Writing,” Selected Poetry and Prose of Anna Barbauld, ed. William McCarthy and Elizabeth Craft [Peterborough, Ontario, 2002], 407, 377); and Byron, who accepted that readers had the ultimate power to decide—at the end of Canto I of Don Juan, he told his readers that he would only write more, and thus they would only “meet again, if we should understand / Each other”: Lord Byron: The Major Works, ed. Jerome McGann (Oxford, 2000), p. 143 (canto 1, stanza 222, lines 765–66). William St. Clair The Reading Nation in the Romantic Period cambridge: cambridge university press, 2004. xxix + 765 pages isbn: 978-0-521-81006-7
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 | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.166 | 0.049 |
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".