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Record W1583558714

Creolization and the Collective Unconscious: Locating the Originality of Art in Wilson Harris's Jonestown , The Mask of the Beggar and The Ghost of Memory .

2008· article· en· W1583558714 on OpenAlexvenueno aff
Lorna Burns

Bibliographic record

VenuePostcolonial text · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American and Latino Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCreolizationOriginalityCollective unconsciousHybridityUnconscious mindConsciousnessPhilosophyAestheticsSociologyLiteratureEpistemologyLinguisticsPsychoanalysisArtAnthropologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

Alongside the essays and fiction of A‰douard Glissant, Wilson Harris's writings stand as one of the most important contributions to Caribbean creolization theory. Drawing from the philosophical projects of both authors, this essay argues that while creolization has typically been cast as a process of cultural, linguistic, and racial mixing akin to hybridity, it should, rather, be understood as providing a paradigm for the shifting structural relations necessary for the generation of genuinely original forms. As such, it has great significance for imaginative and literary production, and provides a framework for my readings of Harris's novels, Jonestown (1996), The Mask of the Beggar (2003), and The Ghost of Memory (2006), which explore the creative potential of creolization as a dialogue between consciousness and, what Jung and Harris refer to as, the collective unconsciousness. This essay brings into focus Harris's use of Jungian-inspired concepts, such as archetypes and the collective unconscious, in a development of creolization theory as a imaginative response to historical trauma and the generation of originality in art.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.021
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.001
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 head0.013
GPT teacher head0.265
Teacher spread0.252 · 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
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

Citations4
Published2008
Admission routes1
Has abstractyes

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