English Hegemony, Anglo privilege and the Promise of ‘Allo’lingual Citational Praxis in Transnational Feminisms Research
Bibliographic record
Abstract
Japanese women have been collaborators in Japan's aggression in other Asian countries for over a hundred years.The present struggles of the women in these countries make this fact even clearer to us.… We want to express our sincere apologies to our Asian sisters.We want to learn from and join in their struggles. 'Sengen,' Ajia onnatachi no kai (Declaration of the Asian Women's Association)Tokyo, Japan, 1 March 1977Anglo-academic discussions of transnational feminisms often under-acknowledge transnational feminist activist knowledges, epistemologies, texts, linguistic labours and non-Anglophone feminist thought.The knowledge practices involved in everyday transnational women's activism and required for the translation of feminist activist thoughtreading, interpreting, summarising, translating and editing-are forms of linguistic and intellectual labour through which feminist ideas can travel transnationally.I learned this by spending a number of years elbow-deep in activist texts, 1 not as a researcher but as a language worker (translator, interpreter, language teacher) in pre-internet era, Japan-based transnational feminist organising (Lunny, 1995).In the early 1990s, feminist groups in Asia were developing the discourses and strategies of women's human rights, a process involving significant cultural and linguistic translation (See Josei no jinken iinkai [Women's Human Rights Committee] and Saito, 1994).I learned then to think of transnational feminisms and transnational feminist thought as: 1) emerging out of in/formal networks and grassroots women's movements; 2) developed and 817719F ER0010.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".