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Record W4213163746 · doi:10.7202/1086331ar

La vengeance chez Frédéric Marcelin et Sony Labou Tansi : La vengeance de Mama (1902, 1974) et La Vie et demie (1979)

2022· article· en· W4213163746 on OpenAlexaff
Joubert Satyre

Bibliographic record

VenueDalhousie French Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicCaribbean and African Literature and Culture
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHumanitiesTheme (computing)Plot (graphics)ArtArt history

Abstract

fetched live from OpenAlex

Nearly 70 years apart, two francophone authors, the Haitian Frédéric Marcelin (1848-1917) and the Congolese Sony Labou Tansi (1947-1995), published novels whose plot either entirely or partially calls upon the theme of vengeance, each featuring the same principal elements: women, dictators, champagne, poison, seduction and sex. In Marcelin’s La vengeance de Mama (1902, 1974), Zulma Corneille, nicknamed Mama, avenges the death of her fiancé, Épaminondas Labasterre, by making his murderer Télémaque drink poisoned champagne during an amourous rendez-vous; in Sony Labou Tansi’s La Vie et demie (1979), after seeing her entire family murdered by the Guide Providientiel de la Katamalanasie, Chaïdana, the daughter of the antagonist Martial, likewise uses poisoned champagne to kill off a number of the totalitarian country’s officials after having offered herself to them in the novel’s eponymous hotel. The goal of this article is to investigate what must be fortuitous similarities between these two novels, as it is unlikely that Labou Tansi would have read Marcelin. It aims to analyse the way in which vengeance is employed in the novels, notably the use of ruses and seduction as a means of enticing the victims.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.725
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.271
Teacher spread0.248 · 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.

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
Published2022
Admission routes1
Has abstractyes

Explore more

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