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Record W2015963710 · doi:10.1177/0959354310364205

Incorporating Realist Fiction into Dialogical Theories of the Self

2010· article· en· W2015963710 on OpenAlexaff
Joseph L. Mills

Bibliographic record

VenueTheory & Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDialogical selfContext (archaeology)CriticismEpistemologyRealismSociologyLiteratureOrder (exchange)Literary criticismPhilosophyPsychoanalysisHistoryPsychologyArt

Abstract

fetched live from OpenAlex

The study of realist fiction can illuminate and expand dialogical theories of the self, especially those originating in M.M. Bakhtin’s writings. To overcome the criticism that the study of the literary criticism surrounding major works of fiction has no place in psychology and needs no input from it, I advance the concept of the Edited Other. The concept states that, in analytic and related forms of psychotherapy, specific and paramount modes of self-presentation are represented within the context of theoretical constructs, while, in works of realist fiction, authors isolate characters’ dominant characteristics within the context of novels’ plots. To instantiate the Edited Other I choose one of Mario Vargas Llosa’s novels ( The War of the End of the World). I select Vargas Llosa because of his mastery of varied forms of novel, his well-developed moral philosophy, and his deep understanding of literature’s role in society. Furthermore, The War of the End of the World, almost uniquely, can be compared to a supposedly factual account of the events portrayed in the novel (Euclides da Cunha’s Rebellion in the Backlands). I use the Edited Other in order to demonstrate that Vargas Llosa, by using fictional characters, provides contemporary readers with bridges linking them to and giving them imaginative access to historical events.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.022
GPT teacher head0.371
Teacher spread0.349 · 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.

Study designTheoretical or conceptual
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

Citations14
Published2010
Admission routes1
Has abstractyes

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