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Record W4409239794 · doi:10.1515/cat-2025-0004

The Recovery of Self in Emotional Authenticity: Kazuo Ishiguro’s <i>Klara and the Sun</i>

2024· article· en· W4409239794 on OpenAlexaff
Jack Robinson

Bibliographic record

VenueCulture as Text · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicContemporary Literature and Criticism
Canadian institutionsMacEwan University
Fundersnot available
KeywordsPhysicsPsychologyAstrophysicsPhilosophy

Abstract

fetched live from OpenAlex

Abstract The novel is a fable about the amelioration of human behavior and a cautionary tale about the paradigm of rationality with its corresponding devaluation of emotion. It depicts the AI narrator Klara in a mechanized rural American society of the near future. Klara’s role is to provide affectionate care for a genetically modified or “lifted” middle-class teenager, to balance her improved intelligence with a schooling in consideration for others. The novel satirizes the contradiction of treating the apparently non-human but inwardly altruistic as alternately human and sub-human. Learning about human emotion and ethics as she goes, Klara becomes compassionate, patient, and loving. Since she hopes that her charge, made seriously ill by the genetic editing process, will survive, she expresses that hope through her faith, which is comically modelled on human assumptions about faith that she learns from observation. Klara helps those humans close to her to recover their authentic emotional selves to the limited degree that their enculturation permits, unveiling the depression caused by unawareness of universal emotional needs. Her narrative of embodying love and faith amidst mechanized humans reclaims the innocence of the child and the lamb, as emphasized by the novel’s Blakean tone and allusions. The unwaged Klara in this novel dedicated to the author’s mother represents the idealization and corresponding relegation of a subtle and mature management of emotion to the caregivers of the female gender; ironically, it also points out the universal human value of non-judgment and openness toward love.

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: Empirical · Consensus signal: none
Teacher disagreement score0.892
Threshold uncertainty score0.535

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 studies0.0000.000
Scholarly communication0.0010.000
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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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
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
Published2024
Admission routes1
Has abstractyes

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