Bibliographic record
Abstract
This chapter provides an introduction to the work of the novelist Dany Laferrière. Born in Port-au-Prince in 1953, Laferrière was forced to flee Haiti in 1976. He immigrated to Montreal and published his first novel, Comment faire l’amour avec un Nègre sans se fatiguer , in 1985. His literary début established his irreverent and often provocative treatment of themes including migration, race, and sex. Despite Laferrière’s background and the autobiographical material of his work, he rejects labels such as “migrant,” “exile,” or “postcolonial” and prefers to be read as a nomad and as an author recognized for his craft over his political engagement. This chapter discusses literary fields that overlap with Laferrière’s writing and offers an overview of his works, especially his ten-volume Autobiographie américaine , which gives a semi-autobiographical account of his childhood in Haiti, his immigration to Montreal, and his return visit to Haiti. This chapter also examines the significance of Laferrière’s election to l’Académie Française and his recent turn to graphic novels.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.057 | 0.017 |
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".