Changer de refrain. Redécouvrir Haïti dans <i>Il faut parfois chanter</i> d’Évelyne Trouillot
Bibliographic record
Abstract
Même si Évelyne Trouillot s’est illustrée dans de nombreux genres littéraires et a reçu de multiples distinctions, ses oeuvres demeurent relativement peu étudiées hormis deux romans, Rosalie l’infâme (2003) et La mémoire aux abois (2010). Cet article souligne le rôle indiscutable que joue la poésie d’Évelyne Trouillot dans l’esquisse d’une nouvelle vision d’Haïti. Il s’agit précisément d’examiner la manière dont se déploie un processus de remémoire tout au long des pages de Il faut parfois chanter (2023) afin d’offrir un portrait en clair-obscur de ce que signifie vivre avec et lutter contre le legs de l’exploitation coloniale française en Haïti. Ce recueil de poèmes se singularise ainsi par un retour au passé qui remet en cause la stigmatisation médiatique de la terre natale de la poète et réaffirme l’humanité, l’agentivité et la fierté des marronnes et des marrons de l’histoire qui osent, en chantant, défier la colonialité du savoir.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".