Re-Arranging Translation Culture in North America: What Could Literary Translation Gain from the Music World?
Bibliographic record
Abstract
Literary translation and music arrangement perform the same task: both take original texts or songs and re-work them for new contexts. In Anglo-American culture, though, the similarity ends there. The role that fluency plays in the reception of translations as opposed to arrangements reveals that, between the literary and musical worlds, audiences take very different outlooks on the relationship between an original work and its derivative work. A comparison between Lawrence Venuti’s views on linguistic fluency in translation, as presented in The Translator’s Invisibility (1995), and a case study on fluency (i.e. culturally-perceived musicality) in the arrangements of American a cappella pop group Pentatonix reveals that, where Anglo-American audiences approach translations to lock onto an original text, the same audiences view arrangements as authentic, distinct developments in an original song’s creative evolution. Having identified this problem in literary translation discourse, this paper turns to Louise M. Rosenblatt’s transactional reader response theory and Roland Barthes’ notion of the death of the author as critical frameworks for rethinking originality and the development of a text or song’s afterlife. This paper considers a different way of thinking about the relationship between readers, “original” texts and songs, and their derivative works, and goes on to suggest that Anglo-American readers would do well to take a more critical perspective on the process of translation.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.015 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".