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Record W2287724385 · doi:10.5539/ells.v6n1p28

Metafictional Dialogism in O. Henry’s Short Stories

2016· article· en· W2287724385 on OpenAlexvenueno aff
Chin Ching Lee

Bibliographic record

VenueEnglish Language and Literature Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicRussian Literature and Bakhtin Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPolyphonyHeteroglossiaIntertextualityLiteratureIdeologySociologyAppropriationNarrativeHegemonyCapitalismMetanarrativeImpromptuAestheticsPhilosophyArtLinguisticsLawPoliticsPolitical science

Abstract

fetched live from OpenAlex

<p>According to Mikhail Bakhtin, language is ideologically saturated. The verbal constructs—novelistic discourses as “hybrid constructions” here—are loci where centripetal and centrifugal forces collide. Authorial speech, narrator’s speech, and also characters’ speech are interwoven in the text to exhibit diverse ideas, and to disclose polyphonic textualities. In light of Bakhtin’s aforementioned idea, this paper will discuss O. Henry’s attempts to orchestrate “the voices of the city” in four short stories: “The Gift of the Magi,” “An Unfinished Story,”, “Mammon and the Archer,” and “An Unfinished Christmas Story.” New York is portrayed as an ambivalent setting of prosperity and poverty, of dreams built up and broken. Literary devices such as twist endings, parodic adaptations and incorporated genre not only lay bare the textual fictitiousness, but question the permanency of social systems such as capitalism. In addition, the narrators’ descriptions evoke concerns for the exploited within the text, while the self-reflexive authorial intrusions make comments on the hegemonic capitalism with-out. O. Henry, who “speaks through language,” does succeed in creating texts of heteroglossia. Humanistic compassion for the exploited proletarian and social censure against capitalist violence are both displayed.</p>

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.317
Teacher spread0.301 · 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 designQualitative
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
Published2016
Admission routes1
Has abstractyes

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