Naturalness in the Spanish Dubbing Language: a Case of Not-so-close Friends1
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
The present article examines the Spanish dubbing language from the point of view of its naturalness. The premise is that dubbing language is best analyzed by comparing it to the register it imitates, as long as its peculiar features are taken into consideration. This study is divided into two parts: firstly, a description of the features that make dubbing dialogue different from real dialogue, focusing on those arising from the source text; secondly, a comparative analysis of dubbed and real dialogue. In the latter, a corpus of spontaneous conversations will be used as a yardstick for natural dialogue and the main strategies used in colloquial conversation will provide the linguistic units to be analyzed: intensifiers and discourse markers. The main unidiomatic features detected are the use of anglicisms, especially at the pragmatic level, and a certain shift in tone that may cause a variation in the relation among the participants in the dubbed text. Finally, the notion of suspension of linguistic disbelief is put forward as a possible explanation for the perpetuation of unnatural features in dubbing language.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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