Bibliographic record
Abstract
Nietzsche, Kierkegaard, Virginia Woolf, Samuel Taylor Coleridge, André Breton, Rousseau, Simone de Beauvoir: who could imagine a better group of walking companions? In this engaging and invigorating book, Bruce Baugh takes us on a philosophical tour, following in the footsteps and thoughts of some great philosophers and thinkers. How does walking reveal space and place and provide a heightened sense of embodied consciousness? Can walking in André Breton’s footsteps enable us to "remember" Breton’s experiences? A chapter on Sartre and Beauvoir investigates walking in relation to anxiety and our different ways of responding to our bodies. Walking in the Quantocks, Baugh seeks out the connection between Coleridge’s walking and his poetic imagination. With Rousseau and Nietzsche, he examines the link between solitary mountain walks and great thoughts; with Kierkegaard, he looks at the urban flâneur and the disjunction between outward appearances and spiritual inwardness. Finally, in Sussex and London, Baugh explores how Virginia Woolf transposed a Romantic nature pantheism to London in Mrs. Dalloway. Philosophers’ Walks provides a fresh and imaginative reading of great philosophers, offering a new way of understanding some of their major works and ideas.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.009 |
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".