Writing In Between Worlds: Reflections on Language and Identity from Works by Nancy Huston and Leïla Sebbar
Bibliographic record
Abstract
This article analyzes the themes of language, cultural heterogeneity, and writing as liminal space in autobiographical nonfiction texts by Canadian-born bilingual author Nancy Huston and Algerian-born French writer Leïla Sebbar. In their coauthored correspondence on the theme of exile, Lettres parisiennes: Autopsie de l’exil, Huston and Sebbar describe writing as a land or territory, a place of one's own, and Sebbar defines exile as the very foundation of her being. Each writer explores the meaning of language in her life (English and French for Huston, French and Arabic for Sebbar), particularly as it relates to childhood and loss. Other themes include the construction and performance of self through language and writing; mobility, even instability, as vital constituents of identity; and exile and difference as freedom. While “exile” for these authors is not a question of forced migration, their reflections on living in between and across cultures—in the fault lines—have rich resonance for theorists, writers, travelers, and users of language in a globalized world.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.038 | 0.026 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".