Activism in translation: Yan Fu’s translational activism against foreign imperialism in late Qing China
Bibliographic record
Abstract
The concept of translational activism underscores the ways translation has been used to promote social change. Translation and activism as an emerging area of interest in Translation Studies have attracted growing scholarly attention. Nevertheless, few studies have been conducted on activist translation in the context of China. This study examines translational activism against foreign imperialism through a case study on Yan Fu, a pioneer activist translator in late Qing China. Tymoczko’s concepts of resistance and engagement are used as descriptive categories for the empirical analysis. The appraisal framework is adopted as the analytical tool to address Yan Fu’s positioning and activist intervention. It is found that Yan pursued two complementary forms of activism in his translation: Yan demonstrates his resistance to foreign imperialism by criticising foreign aggression and resisting imperial privileges; while Yan manifests his engagement by disclosing the national crisis, inspiring patriotism and calling for action. As textual intervention has received little attention in activist translation, the present study fills this gap by examining the linguistic and textual manifestations of Yan’s activist intervention. In addition to applying the new theoretical lens of activism to examine Yan’s translation practice, the present study makes a theoretical contribution by adopting the appraisal framework in the area of translation and activism.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".