Od przekładu do twórczości, czyli o quebeckich feministkach, anglokanadyjskich tłumaczkach i przekładowym continuum
Bibliographic record
Abstract
From Translation to the Writing: On the Quebec Feminists, Anglo-Canadian Women Translators and the Translation ContinuumThe article presents the unique relationship between French- and English- -speaking translators in Canada, which has resulted in a great number of interesting translation phenomena. The author makes reference to the distinction between feminist translation and translation in the feminine, derived from literature in the feminine, both widely practiced in Quebec. One of the representatives of this trend was Suzanne de Lotbiniere-Harwood, mostly French-English translator, known for her translations of Nicole Brossard’s works. Her activity, as well as that of other translators, contributed to the spread of the idea of translation in the feminine among Canadian writers and theoreticians. What is more, their cooperation has resulted in the creation of the magazine Tessera and in the emergence of a range of phenomena on the borderline between translation and literature. This relationship is also a rare example of the impact of “minor literature”, which is the literature of Quebec, on the English-language Canadian literature.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.017 | 0.021 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".