Bibliographic record
Abstract
Lord Byron took a highly ambivalent attitude toward female authorship, and yet his poetry, letters, and journals exhibit many proofs of the power of women’s language and perceptions. He responded to, borrowed from, and adapted parts of the works of Maria Edgeworth, Harriet Lee, Madame de Staël, Mary Shelley, Elizabeth Inchbald, Hannah Cowley, Joanna Baillie, Lady Caroline Lamb, Mary Robinson, and Charlotte Dacre. The influence of women writers on his career may also be seen in the development of the female (and male) characters in his narrative poetry and drama. This essay focuses on the influence upon Byron of Lee, Inchbald, Staël, Dacre, and Lamb, and secondarily on Byron’s response to intellectual women like Lady Oxford, Lady Melbourne, as well as the works of male writers, such as Thomas Moore, Percy Shelley, and William Wordsworth, who affected his portrayal of the genders.
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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.026 | 0.052 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".