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Record W4408533983 · doi:10.5430/wjel.v15n4p301

Isolation, Loneliness and Identity: A Literary Exploration

2025· article· en· W4408533983 on OpenAlexvenueno aff
Akram Shalghin

Bibliographic record

VenueWorld Journal of English Language · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessIsolation (microbiology)Identity (music)Computer sciencePsychologyAestheticsArtSocial psychologyBiology

Abstract

fetched live from OpenAlex

This research paper explores the intricate relationship between isolation and identity in five seminal literary works: Robinson Crusoe by Daniel Defoe, The Bet by Anton Chekhov, The Metamorphosis by Franz Kafka, A Rose for Emily by William Faulkner, and The Old Man and the Sea by Ernest Hemingway. Through a comparative analysis of the protagonists—Robinson Crusoe, the solicitor, Gregor Samsa, Emily Grierson, and Santiago—this study examines how physical, emotional, and existential isolation shapes their identities. The findings reveal that isolation is a multifaceted experience, capable of fostering profound self-discovery, spiritual growth, and intellectual enlightenment, while also leading to alienation, despair, and a loss of human connection. This research underscores the dual nature of isolation, which simultaneously offers opportunities for self-reflection while challenging one's sense of self, ultimately shaping the characters' identities in complex and sometimes contradictory ways.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.013
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0130.018
Scholarly communication0.0100.006
Open science0.0010.007
Research integrity0.0010.002
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 head0.011
GPT teacher head0.250
Teacher spread0.239 · 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
Published2025
Admission routes1
Has abstractyes

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