Bibliographic record
Abstract
There are three wars in the mind and in the art of William Faulkner--the American Civil War, World War I, and World War II. Although he did not fight in any war, he postured as a veteran flyer, for he had enlisted in the Royal Flying Corps in Canada. In his novels, short stories, essays, and letters, war remained a looming subject. Faulkner and War, a collection of essays from the Faulkner and Yoknapatawpha Conference, held at the University of Mississippi in 2001, explores the role that war played in the life and work of a writer whose career seems forever poised against a backdrop of wars going on or recently ended or in the volatile years between. Perhaps most significant for all his works was the Civil War, which had ended thirty-two years before Faulkner was born. Yet it was the vast, escapable panorama against which he set his novels of the anguished South. John Limon discusses Faulkner's attempt to show how much of the sense of reality that the Great War produced could be rendered in fiction without explicit reference to it, as, for example, in one novel seemingly remote from the war, As I Lay Dying. Lothar Hoennighausen examines Faulkner's evolving ideological attitudes toward war in Soldiers' Pay, A Fable, and The Mansion. These and other essays give illumination to Faulkner's close analysis of war and its consequences as they appear in his work. Noel Polk, a professor of English at the University of Southern Mississippi, is the author of Children of the Dark House: Text and Context in Faulkner, Eudora Welty: A Critical Bibliography, Outside the Southern Myth (all from University Press of Mississippi), and other books. Ann J. Abadie, co-editor of publications in the Faulkner and Yoknapatawpha Series, is associate director of the Center for the Study of Southern Culture at the University of Mississippi.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".