<scp>Leah Orr</scp>. <i>Publishing the Woman Writer in England, 1670–1750</i>
Bibliographic record
Abstract
How do we conceptualize, and how do we quantify, women’s writing between the Restoration and the mid-eighteenth century? While authors like Behn, Haywood, Cavendish, Manley, Centlivre and Rowe are central to feminist criticism of the long eighteenth century, there are significant gaps in the historical record to which Leah Orr’s book attends. In her previous book, Novel Ventures (2017), Orr surveys nearly 500 works to challenge ‘rise of the novel’ narratives that are based on a limited canon of familiar names. Now, Publishing the Woman Writer in England, 1670–1750 identifies nearly 700 works—673 to be exact—ostensibly written by a female author, based on attributions from the English Short-Title Catalogue. Orr’s comprehensive research allows her to refute erroneous claims about women’s writing during this period. According to the numbers, there was a steady flow, rather than a rise or fall, of female-authored publications from the 1670s to the 1740s (pp. 20–21). Nor is it true that women writers mainly published fiction. Rather than novels, poetry and plays, most of Orr’s finds are ‘advice books, recipe books, a great deal of religious writing, political writing, memoirs, letters, and histories’ (p. vi). Lastly, Orr’s statistics undermine the ‘traditional view’ that early women writers faced ‘social hazards’ when publishing under their own names. In fact, more than half of the 673 works ‘provide a name (not necessarily real) that is clearly female as the author’ (p. 20). Orr suggests that publishers used female honorifics, initials and names on title pages as a marketing strategy to garner interest and sell copies.
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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.494 | 0.329 |
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".