Highlighting Difficulties in Idiomatic Translation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Idioms are fixed phrases with little to no possible syntactic reconfiguration, whose lexemes are not representative of the meaning they convey in any given language. Their complexity is rooted in deep semantic structures from ages of cultural history. In translation, idioms pose great difficulty due to their innate dichotomous nature and deep cultural roots. For an idiom to be translated from the source language into the target language, an equivalent idiom must be found in the target language in order for the translated idiom to have the same effect on the audience. This paper examines three English and German idioms in comparison to determine what allows for equivalency between translated idioms. Between the three levels of equivalence, strong, weak, and zero equivalence, there are different factors that add to the complexity of translation and their counterparts in translation. In this paper, I explore three levels of idiomatic equivalence and discuss how these three levels are different from each other.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it