Bibliographic record
Abstract
The year 2022 marked the twenty-fifth anniversary of the publication of Helen P. Bruder’s William Blake and the Daughters of Albion (Macmillan, 1997) (hereafter WBDA), the first book that brought feminist criticism to bear on Blake studies. Bruder’s WBDA wrestles with Blake’s complex representations of gender and sexuality. While earlier essays brought much-needed critical focus to Blake’s representations of women (see Susan Fox and Anne Mellor), Bruder’s book-length study argued for a radical feminist spirit in his works. This strident call to arms would advance Blake scholarship in exciting new directions, and WBDA has been widely cited ever since. Bruder is also the editor of Women Reading William Blake (Palgrave Macmillan, 2007) and prolific co-editor with Tristanne Connolly of four collections: Queer Blake (Palgrave Macmillan, 2010), Blake, Gender and Culture (Pickering & Chatto, 2012), Sexy Blake (Palgrave Macmillan, 2013), and Beastly Blake (Palgrave Macmillan, 2018). Currently, she is an independent scholar living in Oxfordshire. I met with her on 3 October 2022 at St. James’s Church, Piccadilly, in London, where we talked in the vestibule near the font where Blake was baptized in 1757. In the interview that follows, Bruder reflects on WBDA and what has changed in Blake scholarship since then.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".