Conversations with James Salter
Bibliographic record
Abstract
James Salter (1925-2015) has been known throughout his career as a writer's acclaimed by such literary greats as Susan Sontag, Richard Ford, John Banville, and Peter Matthiessen for his lyrical prose, his insightful and daring explorations of sex, and his examinations of the inner lives of women and men. Conversations with James Salter collects interviews published from 1972 to 2014 with the award-winning author of The Hunters, A Sport and a Pastime, Light Years, and All That Is. Gathered here are his earliest interviews following acclaimed but moderately selling novels, conversations covering his work as a screenwriter and award-winning director, and interviews charting his explosive popularity after publishing All That Is, his first novel after a gap of thirty-four years. These conversations chart Salter's progression as a writer, his love affair with France, his military past as a fighter pilot, and his lyrical explorations of gender relations. The collection contains interviews from Sweden, France, and Argentina appearing for the first time in English. Included as well are published conversations from the United States, Canada, and Australia, some of which are significantly extended versions, giving this collection an international scope of Salter's wide-ranging career and his place in world literature.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".