Bibliographic record
Abstract
The expression "littérature migrante," coined by Québécois critics in the mid-1980s, reflected the emerging body of literary works written by recent immigrants to the province. Redefining the concept of migrancy, Subha Xavier’s The Migrant Text argues that global movements of people have fundamentally changed literary production over the past thirty years. Bringing together a corpus of recent novels by immigrants to France and Quebec, Xavier suggests that these diverse works extend beyond labels such as francophone or postcolonial literature to forge a new mode of writing that deserves recognition on its own terms. Weaving together literary theory and salient examples taken from numerous French-language novels, The Migrant Text shows how both external and internal factors shape migrant writing in contemporary French literature. The opening chapters trace the elusive concept of the migrant as it appears in extant theories of nationalism, postcolonialism, world literature, and francophonie. What follows are incisive analyses of fiction written for French audiences by authors from Algeria, Cameroon, China, Haiti, Iraq, and Poland, whose works reveal that the processes of troubling national categories and evading colonial power dynamics can be wellsprings for creativity. One of the most pressing social and political topics of our day, immigration challenges our ideas about homeland and citizenship. Celebrating the courage and tenacity of immigrants from around the world, The Migrant Text carves a new space for discussing the dynamics of global literature.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.228 | 0.079 |
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".