Bibliographic record
Abstract
This essay deals with Nina Bouraoui&s;s mixed-race ( métis ) identity as presented in her autobiographical novels Garçon manqué and Mes mauvaises pensées . The métis question takes the shape of a representation of an ethnicized, dual and fractured identity. My argument explores a contradiction at work in Bouraoui&s;s texts: while reclaiming the existence of a Franco-Algerian métis identity, Bouraoui represents the métis as the incarnated perpetuation of the historical tensions that divided France and Algeria. The narratives simultaneously construct and deconstruct Bouraoui&s;s Franco-Algerian métis identity. I examine how Bouraoui represents her Algerian legacy and appropriates a familial history to construct herself as Algerian. I analyze how traumatic memories of asphyxiation are a metaphor for Bouraoui&s;s difficult relationship with her French self, symbolized by the motif of white skin. And I consider how the ends of the two novels provide a problematic acceptance and fulfillment of Bouraoui&s;s métis identity.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".