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Record W2313268928 · doi:10.1093/notesj/gjs135

Joseph Fruscione, Faulkner and Hemingway: Biography of a Literary Rivalry.

2012· article· en· W2313268928 on OpenAlexaboutno aff
Mimi Reisel Gladstein

Bibliographic record

VenueNotes and Queries · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican and British Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCadetBiographyRivalryParallelsHEROBattleOfficerHistoryLiteraturePerformance artArtArt historyPsychoanalysisPsychologyAncient historyArchaeology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0170.013
Scholarly communication0.0080.010
Open science0.0020.003
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0080.002

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.

Opus teacher head0.012
GPT teacher head0.206
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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