Cartographies urbaines et poétique(s) des marges dans Petit Piment (2015) d’Alain Mabanckou et La Pièce d’or (2006) de Ken Bugul
Bibliographic record
Abstract
Dans Petit Piment (2015) d’Alain Mabanckou et La Pièce d’or (2006) de Ken Bugul, la ville postcoloniale africaine dessine des frontières qui sont l’occasion pour les auteurs de réfléchir aux enjeux mobilisés par la marginalisation des personnages au sein de leurs sociétés respectives. Dans le cadre de cet article, nous nous proposons de voir dans quelle mesure les cartographies urbaines déployées dans ces deux romans forgent une poétique des marges à travers laquelle les écrivains interrogent, chacun à leur manière, le rôle de la littérature dans la lutte contre les injustices sociales et le pouvoir de la parole dans le processus de réappropriation de l’espace par ceux qui en sont exclus. La « dialectique socio-spatiale » d’Edward Soja.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
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".