Translation as Craft, as Recovery, as the Life and Afterlife of a Text: Sujit Mukherjee on Translation in India
Bibliographic record
Abstract
Sujit Mukherjee passed away in 2003, having been an outstanding intellectual figure in India and beyond. A writer himself, but most of all a translator, Mukherjee contributed greatly to stirring the debate and reflection on translation in India. Although he quite humbly declared, on several occasions, that India never had such a thing as a theory of translation, his books and articles have traced the history of this activity and given shape to a metadiscourse on translation which is far from the abstractions of theories and full of the strength of the enlightened practitioner’s point of view. Mukherjee’s approach to the observation of translation practices is permeated by his modesty, his brisk simplicity and, above all, his relentless positivity. In his words, translation becomes a dynamic, pervasive and constructive practice, far from the subordinate and derivative essence so often ascribed to it by Western scholars. This paper brings to the fore the non-theories of Sujit Mukerjee and proceeds by discussing them along a chronological axis. Organized in three sections, the paper first analyses Mukherjee’s viewpoint on translation in India before the British, to then move onto translation and the role of English during and after colonization. The third and final section offers a comparison between Mukherjee’s ideas and reflections and those by three outstanding Western translation scholars.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.017 | 0.025 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".