Metamorphosis or Metramorphosis? Towards a Feminist Ethics of Difference in Translation
Bibliographic record
Abstract
Translation has been theorized as a process of metamorphosis, either as metaphor (replacing the original) or metonymy (substituting part for original whole). I propose an additional model for translation exchanges: the metramorphic processes described by psychoanalyst Bracha Ettinger. Ettinger expands the scope of interactions by describing maternal/late pre-natal infant relations as ‘subjectivity-as-encounter.’ Her focus on a ‘severality’ preceding autonomous subject positions overcomes the problematic self/other divide and helps us rethink the relation between source and target text. Ettinger posits ‘matrixial’ metramorphosis, which, unlike metamorphosis, does not involve total transformations; rather, it indicates expansion or development. Textually, this means that translations do not efface sources through equivalent matches or inevitable losses, but extend them through exchanges in which sources are still present within translations. An alternative to equivalence as the goal of translation and fidelity as the ethics of translation, a matrixial paradigm reflects the dependency of the source text on the translation, as well as the plurality of many texts prior to translation. A metramorphic translation practice amplifies source texts, mediating them through a less polarized and more interconnected perception of difference which is the grounds for a new feminist ethics.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.057 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".