Subtitling Taboo Language: Using the Cues of Register and Genre to Affect Audience Experience?
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
Using French-English/English-French examples, this article puts forward the hypothesis that, in the film genre of social realism (depicting low socio-economic groups), subtitlers use linguistic and visual cues which are embedded in genre to trigger audience reactions to representations of taboo language. Examples of the subtitling of taboo language are drawn from three films and the hypothesis above will be explored along three main interrelated axes: i) the value of treating subtitles as an entire system; ii) the relationship between the specific film genre of social realism (depicting low socio-economic groups) and audience perceptions of taboo language use; and iii) discourse representations through register and its effect on characterisation. Nuances are brought to evidence from existing research which argues that the choices relating to taboo language made in the oral to written mode shift are subject to politeness restrictions in terms of register, and that these choices have a homogenising/levelling effect on characterisation (Lambert 1990; Taylor 2006a; Mailhac 2000 for example).
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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