Bibliographic record
Abstract
This contribution is an essay in Translation and Translation Studies, rather than a critical review article, and it is written in Italian. The reasons for both circumstances follow below. 1.to present to the Italian-reading public some specimens — 5 poems — from a new (as yet unpublished) translation into Italian of the modernist master of German-language poetry R. M. Rilke's Sonette an Orpheus (1922); and2.to illustrate to the Italian-reading public — well-versed, for cultural reasons, in 20th-century avantgarde theory and practice — the specific / curious feature of what could be called Rilke's “anti-futurism”: a combination of his “philanthropy” and “technophobia.” 1.a running presentation and commentary on 5 of Rilke's Sonnets to Orpheus, where presentation and commentary are intercut with the actual quotes (German original + interlinear new Italian translation) to which they refer; and2.an Appendix, where the 5 German originals and the corresponding new translations are re-composed and presented synoptically, facing each other. This contribution being an essay in Translation and Translation Studies, rather than a critical review article, it abstains from developing a scholarly discourse within the specific field of Germanistik, which would anyway not be appropriate for a publication in Italian Studies; and it is written in Italian, since the new unpublished Italian translation must be center stage here both as a product in itself and as a tool to highlight some special features of Rilke so far neglected in previous Italian translations.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.010 |
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".