World writing in French and the dimension of dialogue: the right to choose and the choice to write
Bibliographic record
Abstract
Littrature-monde in French cannot be divorced from world writing in other languages, nor can the choices made by writers in different languages be divided from each other: the right to choose and the choice to write in one or more languages have more in common than first meets the eye. This essay sets out to explore the commonality within a diverse group: non-French natives who write in French, native English speakers who write in a language other than English and writers both in French and English whose writing in those languages is influenced by their own ethnic origins. The examples include several writers: Canadian and Qubcois (Jacques Godbout, Nancy Huston, Larissa Lai), Belgian (Grgoire Polet), Chinese-French (Franois Cheng) and Canadian-Irish (Pdraig Siadhail). The distinction between vrai-faux (an object recognized at some levels as not authentic) and faux-vrai (counterfeit) dilemma also confronts writers who cross linguistic and cultural barriers, leading to the question of what constitutes profound identity as opposed to legal identity in such cases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.050 |
| Scholarly communication | 0.023 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".