Gender, genetics, translation: Encounters in the Feminist Translator's Archive of Barbara Godard
Bibliographic record
Abstract
The article demonstrates the usefulness of textual genetics in corroborating the dynamic, process-oriented concepts of translation developed by feminist translation theorists. Focusing on the Canadian scholar and translator Barbara Godard, the paper examines her translation manuscripts of Nicole Brossard’s L’Amèr: ou le chapitre effrité (1977) and Amantes (1980), published in English as These Our Mothers (1983) and Lovhers (1986). The author argues that genetic analysis has the potential to challenge conventional understandings of translation as a linear transfer of meaning in the exchange of equivalences and that genetics can supply evidence that translation is a multidirectional, recursive and dialogical process of thought and transformation, a creative combination rather than a transparent substitution of meaning. The graphic markings, layerings, and inscriptions on the archival drafts reveal complex intersubjective and interdiscursive foldings at the heart of translation and expose translation as a series of temporal re-readings. They bring into view different encounters and relationalities and reaffirm the view of translation as a cultivation of friendship and collaboration.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.048 | 0.032 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".