Joseph Fruscione, Faulkner and Hemingway: Biography of a Literary Rivalry.
Bibliographic record
Abstract
FRUSCIONE’s detailed exploration of the ongoing competition between these two giants of twentieth-century American literature is a rewarding read. He charts the duel from the 1930s, through an ‘almost’ meeting in 1947 when Hemingway and his friend Toby Bruce stopped off in Oxford on their way from Key West to Michigan and Idaho, through their deaths in the early 1960s, Similarities abound and Fruscione does an admirable job of exploring them in such chapters as ‘Brothers Shooting it Out’ and ‘Rivals, Matadors, and Hunters: Textual Sparring and Parallels’. Setting the scene for the rivalry to come, Fruscione situates each writer’s coming of age, both as man and as writer. Born at the end of the nineteenth century, Faulkner being the elder, each young man had tried to enlist in order to experience ‘the Big Show’. However, neither qualified for the American military and so Hemingway became an ambulance driver in Italy and Faulkner an RAF Cadet in Canada. Hemingway’s traumatic wounding is well-chronicled in both his fiction and biography; Faulkner fabricated a wound and was later a bit embarrassed by his embellishment of his military record. He wore an officer’s uniform and carried a swagger stick although he had only been a cadet. The discussion of early similarities, such as both returning home after World War I in the role of wounded hero, Hemingway’s wounds achieved during a battle and Faulkner’s in a drunken escapade is interesting. Both milked the role for all it was worth, an early instance of each performing his public masculinity.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".