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Record W2169443048 · doi:10.5539/ells.v3n1p42

Jay Gatsby’s Trauma and Psychological Loss

2013· article· en· W2169443048 on OpenAlexvenueno aff
Thi Huong Giang Bui

Bibliographic record

VenueEnglish Language and Literature Studies · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican and British Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFreudian slipPsychoanalysisPerspective (graphical)GirlPeriod (music)HistoryTransition (genetics)AestheticsLiteraturePsychologyArtVisual arts

Abstract

fetched live from OpenAlex

F. Scott Fitzgerald (1896-1940) is regarded as a great twentieth-century American novelist. In many ways Fitzgerald’s legendary life has had a huge impact on critics and readers in overshadowing his great work. The 1920s can be seen as a transition time with a great change in American history from the Victorian period to modern times and with the huge impact of World War I on people’s lives. It is only recently that critics have moved away from studying Fitzgerald’s work as that of a merely superficial and historical writer and examined his works in various other perspectives. In addition to historical and biographical studies, Freudian theory is an important approach to bring a new depth to our understanding of his work. In one of his great novels, The Great Gatsby, Fitzgerald depicts the traumatic losses of a self-made man, Jay Gatsby, who tries to win his idealized girl again. In this paper, the author aimed to examine the losses of Jay Gatsby in the light of Freudian theory to bring a new perspective on the protagonist’s trauma and psychological loss and the reasons why he never escapes from his illusive world.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.018
Scholarly communication0.0050.005
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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
GenreEmpirical

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
Published2013
Admission routes1
Has abstractyes

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