L’écrivain désOrienté ou les aspects de l’estitude (Dumitru Tsepeneag, Nancy Huston, Katalin Molnár)
Bibliographic record
Abstract
Abstract In this article, we aim to study the term Estitude by focusing on books by Dumitru Tsepeneag (The Dustying Word), Katalin Molnár (Lamour Dieu) et Nancy Huston (The Lost North). Coming from three different countries (Romania, Hungary and Canada), these three writers are similar as far as their relation to their new creative language is concerned, in this case French. Making use of the new language first presupposes minimalising the importance of one’s native tongue (Romanian, Hungarian and English), but this minimalisation is inappropriate as it indicates one’s exile. At the same time, adoting the French language may prove to be an opportunity, which allows one to research the origins of writing itself : thus, the exiled writer can profit from lingustic calque, lingustic mistakes, literal translation of proverbs and other expressions of his / her native language, of transcript of orality, etc. Being unable to attach himself/herself to a geographical area, the exiled is condamned to live between two countries (the country of origin and the receiving country), between two languages (the native language and the adopted language) and to suffer from a certain complex of superiority. Having a certain social and political experience, s/he stands out among natives, but s/he always runs the risk of being perceived in the « flagrante delicto of strangeness ».
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".