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Record W4388265119 · doi:10.1017/9781108878272.008

Fitzgerald’s Expatriate Years and the European Stories

2023· book-chapter· en· W4388265119 on OpenAlexaff
John G. Kennedy

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageen
FieldArts and Humanities
TopicAmerican and British Literature Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsExpatriateRomanceHistoryWifeRivalryLiteratureArt historyArtLawPolitical science

Abstract

fetched live from OpenAlex

During the peak of his contemporary popularity, F. Scott Fitzgerald lived abroad – mostly in France – for five years and eight months, much of that time pursuing a frenzied social life that impeded his literary work. His European travels included lengthy stays from May 1924 through the end of 1926 and then from March 1929 through September 1931, as well as a five-month sojourn in mid-1928. On foreign shores he experienced misery and elation: his wife Zelda's romance with French aviator Edouard Jozan; completion, publication, and celebration of his third novel, The Great Gatsby (1925); new friendships with Ernest Hemingway and with Gerald and Sara Murphy; innumerable alcoholic binges and embarrassments; false starts on a fourth novel and increasing self-doubts; domestic rivalry and acrimony; Zelda's first nervous breakdown and treatment; his hotel life and fugitive magazine fiction. Only after returning to the United States did Fitzgerald publish Tender Is the Night (1934), a work that despite its flaws plumbs the paradoxes of desire more profoundly than did Gatsby . Understandably, Tender has preoccupied scholars and biographers seeking insight into the author's life abroad, for its thinly veiled treatment of the Fitzgeralds' domestic calamities, set against the crazy violence of postwar Europe, reveals much about the author's own identification with expatriate culture. But the many short stories set at least partly in Europe likewise merit closer attention, less for their biographical connections than for their representations of the American migration to Europe after World War I.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.889
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.174
Teacher spread0.153 · 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 teacher head, not a consensus.

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

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
Published2023
Admission routes1
Has abstractyes

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