Transferring Culture in Translations — Modern and Postmodern Options
Bibliographic record
Abstract
Transferring Culture in Translations - Modern and Postmodern Options — The characteristic elements of the modern theories of translation by Charles Baudelaire and Sigmund Freud are outlined and described in the context of the question of how differences in culture and understanding can be recognized and translated. Translations depend on a certain homogeneity (between the different sign systems used) which can be provided by the creation of meaning through language. The understanding, acknowledgement and creation of meaning is vital for translations. Both Baudelaire and Freud are quite aware of the relative value of such meaning. In postmodernist theories, translation becomes 'necessarily impossible.' Paul de Man's and Jacques Derrida's practical use of Walter Benjamin's text on translation indeed shows that they do not translate him. They do, however, adapt him to their own view and their specific meaning. More and different meanings can be detected in Benjamin, though, and the necessity for multiple, ambiguous, but not entirely arbitrary translations must be recognized. Only a meaningful, inventive combination of one's own and the other's positions can make cultural transfer and the acknowledgement and tentative understanding of otherness possible.
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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 | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.052 |
| Scholarly communication | 0.012 | 0.022 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| 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".