Strange sisters : literature and aesthetics in the nineteenth century
Bibliographic record
Abstract
Contents: Francesca Orestano: Introduction - Luisa Cale: Belinda and Exhibition Culture: Fiction, Pictures and Imaginary Ekphrasis - Maria Luisa Roli: A Voyage by Balloon: Stifter's Condor - Lucy Bending: 'Fishing in a Strange Element': Harriet Martineau and the Visible World - J.B. Bullen: Mid-Nineteenth-Century British Primitivism and the Continent of Europe - Paola Spinozzi: Journeying through Translation: Dante among the Victorians, Dante Gabriel Rossetti in Medieval Italy - Francesca Orestano: Across the Picturesque: Ruskin's Argument with the Strange Sisters - Alberta Gnugnoli: Famous Men and Fair Ladies: Genius, Creativity and Beauty in the Portraits of Julia Margaret Cameron - Francesca Frigerio: Out of Focus: A Portrait of Charles Lutwidge Dodgson, a.k.a. Lewis Carroll - Graham Smith: Michelangelo's Duke of Urbino in Literature, Travel-Writing and Photography of the Nineteenth Century - Marialuisa Bignami: Sir Joshua and the Historian: Portraits in George Eliot's Daniel Deronda - Hilary Fraser: Through the Looking-Glass: Looking like a Woman in the Nineteenth Century - Elisa Bizzotto: Blurring the Confines of Art and Gender: Aubrey Beardsley's Legend of Venus and Tannhauser, 'The Fragment of a Story' - Linda Goddard: Gauguin's Guidebooks: Noa Noa in the Context of Nineteenth-Century Travel-Writing - Alexandra Harris: The Antimacassar Restored: Victorian Taste in the Early Twentieth 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 | 0.003 |
| Science and technology studies | 0.020 | 0.024 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".