An Introduction to the ‘literary person[s]’ of Anne Lister and the Ladies of Llangollen
Bibliographic record
Abstract
Abstract Anne Lister eagerly looked forward to her tour of North Wales in July 1822 – a tour made in the company of a dear aunt, and whose principal highlight would be a visit to Eleanor Butler and Sarah Ponsonby, the celebrated Ladies of Llangollen. Ten days prior to her departure, Lister received a letter from her friend, Isabel Dalton, reassuring her that apparently ‘no introduction’ to the Ladies would be necessary: “Any literary person especially calling on them would be taken as a compliment.” Butler and Ponsonby were accustomed to receiving visits from the best of ‘literary persons’, including William Wordsworth, Caroline Lamb, Edmund Burke, and Sir Walter Scott. While Lister lacked such illustrious renown, she was certainly qualified to make the visit. Her diaries reveal that Halifax Library was one of her regular haunts, that she kept careful note of her reading, regularly perused literary reviews, and enjoyed performing favourite book passages and songs to friends and family. She relied on her literary knowledge to further her amorous intrigues, was generous in her presentation of bound books as gifts and love tokens, and confided in a select few of her ‘ambition in the literary way’ and related wish for ‘a name in the world’. Unsurprisingly then, the Ladies of Llangollen’s ‘rustic library’ made an immediate impression on Lister, who warmly admired their ‘little bookcase with 30 or 40 little volumes [of] chiefly poetry, Spenser, Chaucer, Pope, Cowper, Homer, Shakespeare, etc. –’. For their part, Butler and Ponsonby were ‘always reading’; or, in their own words, indulging in ‘the exquisite pleasures of retirement and the luxury of purchasing books’. A study of the literary interests and reading practices recorded by Lister and the Ladies of Llangollen offers a valuable extension to our understanding of these fascinating diarists and the importance placed by all three women on the desirability of a literary mindset. In its investigation of the links between textuality and subjectivity, my article considers the meanings associated with different reading spaces, and how the literary pursuits of Anne Lister and the Ladies of Llangollen related to their larger academic interests, attitudes to female education, sexual identity, and financial independence.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.041 | 0.012 |
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".