<scp>Heather Bozant Witcher</scp>. <i>Collaborative Writing in the Long Nineteenth Century: Sympathetic Partnerships and Artistic Creation</i>
Bibliographic record
Abstract
I weed Edith’s garden she mine; then examining each other’s withering heaps we exclaim—‘Well, you might have spared that’ … but the presiding horticulturalist is ruthless … . (p. 157) Katherine Bradley and her niece-lover-collaborator Edith Cooper characterize their compositional practices under their pseudonym ‘Michael Field’ with diverse metaphors: gardening, marriage, mosaic, interlacing like ‘dancing summer flies,’ or ‘murderously cut[ting] away’ (p. 155). Field’s collaborative creative processes and works figure among five case studies in Heather Bozant Witcher’s deeply researched and conceptually innovative contribution to the now extensive scholarship on collaborative writing and relationships. As Witcher’s introductory overview indicates, this scholarship spans historical periods and fields such as life-writing, textual and editing studies, rhetoric and composition, and feminist and queer studies. Studies have explored corporate writing practices in early modern drama, the erotics of male literary partnerships, familial and romantic partnerships, and female partnerships obscured by the dominance of white, heterosexual, male authors. Witcher rightly points out, however, that ‘of the current monographs on literary collaboration, there are none with the broader focus of the nineteenth century’ (p. 5). Addressing this gap, Witcher’s study ranges across ‘Romanticism, Pre-Raphaelitism, Aestheticism, and Modernism’ (p. 7), with in-depth analyses of the ‘sympathetic partnerships’ of Mary Wollstonecraft Godwin and Percy Bysshe Shelley; Christina and Dante Gabriel Rossetti; William Morris, Edward Burne-Jones, and the craftsmen of the Kelmscott Press; Bradley and Cooper as ‘Michael Field’; and Vernon Lee with successive collaborators (A. Mary F. Robinson and the Scottish artist Clementina ‘Kit’ Anstruther-Thomson).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.053 | 0.016 |
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".