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Record W2625881266 · doi:10.3968/9585

Art Regression: On Unconsciousness Trend of The Picture of Dorian Gray

2017· article· en· W2625881266 on OpenAlexvenueno aff
Jiansheng Yan

Bibliographic record

VenueCanadian social science · 2017
Typearticle
Languageen
FieldNeuroscience
TopicAesthetic Perception and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGray (unit)Unconscious mindUnconsciousnessAestheticismPersonalityPsychoanalysisPsychologyPersonality psychologyIndividuationAestheticsSociologyArt

Abstract

fetched live from OpenAlex

As a most important representative of aestheticism, Oscar Wilde holds the view of “art for art sake”. His novel The Picture of Dorian Gray opens the dialogue between art and psychology, which reveals the dual functions of art in shaping personality from the unconscious level. On the one hand, art can bring people aesthetic experience; on the other hand, misreading to art can bring serious damage to both individual and society. By means of psychoanalysis, interpretation to this novel shows that Dorian Gray’s personality split comes from his personal unconsciousness development; his life experience, art obsession and sex impulse directly refer to the three developing stages: inferiority complex, psychological defense mechanism and fear of intimacy. They jointly construct Dorian Gray’s dual personalities. His unconsciousness encourages his desire expansion.

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)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.017
Scholarly communication0.0030.005
Open science0.0000.002
Research integrity0.0010.004
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 head0.028
GPT teacher head0.297
Teacher spread0.269 · 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
GenreOther

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

Citations1
Published2017
Admission routes1
Has abstractyes

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