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Record W2779731723 · doi:10.5539/ass.v14n1p48

Treatment of the Race-Consciousness in Ralph Ellison's Invisible Man

2017· article· en· W2779731723 on OpenAlexvenueno aff
Munther Mohd. Habib

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsnot available
FundersZarqa University
KeywordsInnocenceAssertionHERORace (biology)White (mutation)ConsciousnessPsychoanalysisPsychologyArtPhilosophyLiteratureSociologyGender studiesEpistemologyChemistryComputer science

Abstract

fetched live from OpenAlex

Ralph Ellison's Invisible Man portrays the plight of 'blacks' in America and is a testimony to the fact that the negroes feel disillusioned in a world which is dominated by the white oppressors. Moreover, it is my assertion in the paper that the journey of the un-named hero is a journey from innocence to awareness. The protagonist at the end comes to realize the duplicity of the whites and through his experiences has been successful to convey his individuality.

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)0.002
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.029
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0030.006
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 head0.055
GPT teacher head0.360
Teacher spread0.306 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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