MétaCan
Menu
Back to cohort
Record W2768800582 · doi:10.17576/gema-2017-1704-16

Mimicry of Stowe’s Uncle Tom’s Cabin and the Formation of Resistant Slave Narrative in Ishmael Reed’s Flight to Canada

2017· article· en· W2768800582 on OpenAlexaboutno aff
Zohreh Ramin, Farshid Nowrouzi Roshnavand

Bibliographic record

VenueGEMA Online Journal of Language Studies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMimicryHistoriographyNarrativeWhite (mutation)PostmodernismEssentialismLiteratureSubject (documents)Deconstruction (building)ConsciousnessHistoryRacismSociologyAestheticsArtPhilosophyGender studiesEpistemology

Abstract

fetched live from OpenAlex

Postmodernism has as its major tenet the eradication of master-narratives in favor of marginalized voices. In so doing, it puts forward various strategies which, though different in methodology, are all critical of the dominant exclusionary discourses. Parodic mimicry is one of these subversive strategies which allows the anti-establishment artist to employ the discriminatory discursive practices and skillfully turn them on their heads. African American novelist Ishmael Reed adopts the postmodern technique of mimicry to severely criticize and disrupt the racist structure of the United States. In his “resistant” slave narrative Flight to Canada (1976), he takes to task the traditional historiography, showing how a so-called anti-slavery novel like Harriet Beecher Stowe’s Uncle Tom’s Cabin employs racial essentialism to reinforce the stereotypical representations of blacks and distort history to the benefit of white dominators. Through a parody of Stowe’s canonical work, Reed’s novel provides a space for the black consciousness to serve as an agentic subject and re-narrate the history of slavery, abolitionism and the Civil War. This paper aims to depict how Reed manages to rewrite the history of slavery in Flight to Canada by mimicking Stowe’s Uncle Tom’s Cabin .

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.948

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 communication0.0000.000
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 head0.025
GPT teacher head0.282
Teacher spread0.257 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueGEMA Online Journal of Language StudiesSame topicPostcolonial and Cultural Literary StudiesFrench-language works237,207