Translation, Nationalism and Transnationalism
Bibliographic record
Abstract
I argue that the most efficacious way of establishing a national literature was through the translation of major, high-prestige, foreign texts, such as Greco-Roman epic poetry: translation of Virgil’s poems has had a significant role in creating and honing literary language in European vernaculars and has sometimes served proto-nationalistic and nationalistic agendas. After analysis of the scope of ‘nationalism’ and its relevance to Virgil, I examine examples of the appropriation of cultural authority through translation of the Aeneid in French translations from the sixteenth century, then in other languages including Russian, Hungarian, Portuguese (in both Portugal and Brazil), Catalan, Katharevousa Greek, Maltese and Welsh, with special discussion of the foundational work of Ukrainian literature. I then discuss cases of translation as a proto-nationalist phenomenon, in Hebrew and Argentinian Spanish, and as a transnational phenomenon, in Esperanto. I conclude by relating translation and nation in both outward-looking and inward-looking modalities and in vertical and horizontal dimensions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".