Bibliographic record
Abstract
When Mrs Hurst calls Elizabeth Bennet “an excellent walker,” in Jane Austen’s Pride and Prejudice (1813), the remark is meant to ridicule. For a modern reader, understanding this connotation requires a small exercise in historical imagination. Recent critical studies explore the rise of rambling and the Romantic poets’ penchant for lengthy pedestrian excursions, but Pride and Prejudice does not feature the sort of lonely wanderings that lead to conversations with leech gatherers and mystical mariners. To appreciate the centrality of walking to the novel, we must appropriate Miss Bingley’s question, “What could she mean by it?” Before we can understand the attitudes towards walking and the responses to walking exhibited by characters in the novel—and the function of walking in the plot—it is first necessary to explore the changing place of walking in late eighteenth- and early nineteenth-century society, and the uses of walking in Romantic-era literature. This article examines eighteenth-century accounts of athletic, touristic, sentimental, and performative pedestrianism, including Austen’s attitudes towards her own walks, in order to read walking in the novel.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".