Yeah, that’s it!: Verbal Reference to Visual Information in Film Texts and Film Translations
Bibliographic record
Abstract
This article presents an account of the meaning relationship between visual and verbal information in film and the differences between the conventions of making verbal reference to visual information in English films and their German-language versions. The analysis of a diachronic corpus of popular motion pictures and their German-dubbed versions indicates that the film translations ‘handle’ the co-occurring visual information differently than their English source texts. The translations tend to use alternative, non-equivalent, linguistics structures to refer to visual information and insert additional pronominal references and deictic devices, which overtly connect linguistic items to pictorial elements. As a result, the ongoing spoken discourse is explicitly linked with the physical surroundings of the communicative encounter. In contrast, in the English language versions, the relationship between the verbal utterance and the accompanying visual information more often remains lexically implicit. The shifts in translation affect the ideational, interpersonal, and textual meanings expressed in the film texts which, in turn, may result in a variation in the films’ narrative construction and the realization of extralinguistic concepts, such as, for example, gender relations.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".