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Record W2961028722 · doi:10.29173/jjs75s

“Sonny’s Blues” and Cultural Shadow

2007· article· en· W2961028722 on OpenAlexvenueno aff
Inez Martinez

Bibliographic record

VenueJournal of Jungian Scholarly Studies · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsBluesShadow (psychology)RacismJazzInjusticeAestheticsPityLamentSociologyPsychoanalysisLiteratureArtPsychologyArt historyGender studiesSocial psychology

Abstract

fetched live from OpenAlex

James Baldwin’s short story, “Sonny’s Blues,” portrays a jazz artist’s transformation of an historic and ongoing aspect of America’s cultural shadow, treating black people cruelly as if they were not real. He is enabled to bring about this transformation through his becoming conscious of and owning his personal shadow, treating people regardless of race cruelly as if they were not real. His self-knowledge indicates an equality in the human potential of behaving oppressively and thus frees him from the self-pity and helpless rage of victimization possible to those having suffered the injustice of racism. It thus frees him to create music free of lament, music which in turn frees his brother, who has responded to American racism with repression of his emotions, to feel his grief. Baldwin’s story implies that art, such as the story “Sonny’s Blues,” can express a society’s unjustly caused suffering without lament if the artist has taken responsibility for having him or herself unjustly caused suffering. This art is portrayed as freeing its audience through new consciousness and feeling to develop a new relationship with cultural shadow, one suggesting a beginning of its integration.

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)0.001
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.017
Scholarly communication0.0040.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.042
GPT teacher head0.359
Teacher spread0.318 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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