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Record W1955217376 · doi:10.29173/md22834

Le Mulâtre: A Call to Connection through Narrative Technique

2015· article· en· W1955217376 on OpenAlexaffvenue
Jeff Longard

Bibliographic record

VenueMultilingual Discourses · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature, Film, and Journalism Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNarrativeHumanityTrope (literature)BetrayalLiteratureOppressionDepictionMetanarrativeAgency (philosophy)HistoryArtAestheticsPhilosophyLawPoliticsEpistemologyPolitical science

Abstract

fetched live from OpenAlex

The short story Le Mulâtre (1837) recounts the tragic history of a slave during Haiti’s turbulent 1790s. The first published work of Victor Séjour, it is the first known work of fiction by an African-American writer. At first glance a typical melodramatic tale of brigands, betrayal and revenge, the work is anything but typical in its stark depiction of Caribbean slavery and in its sophisticated use of narration and voice. Written when slavery was still being practiced by both France and the United States, this overt yet sensitive critique is a triumph of the narrative art.This article highlights a modern Structuralist analysis of narration. Séjour not only moves subtly through levels of narration but also through shifts of point of view within discourse and even within speech acts which form an almost unconscious commentary on the action. Moreover, the apparently standard tragic trope is undermined by a complex weaving of life histories in which the triumph of humanity overturns the notion of tragic loss. Thus a story of oppression and inevitability is structured within a voice of commentary, insight, and agency: Séjour succeeds in connecting the humanity on both sides of an inhuman war and in underscoring what is at stake for both master and slave in the continued exploitation of human being by human being.

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)0.011
metaresearch head score (Gemma)0.015
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 score0.020
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0090.047
Scholarly communication0.0200.022
Open science0.0030.011
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0130.002

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 head0.050
GPT teacher head0.318
Teacher spread0.268 · 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
Published2015
Admission routes2
Has abstractyes

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