Quality Control in the Subtitling Industry: An Exploratory Survey Study
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
Quality assurance (QA) and quality control (QC) are central to translation practice and research today, as is translation revision, which, today, is increasingly seen as an integral part of quality monitoring. Revision is also explicitly mentioned as a quality requirement in the European Standard for Translation Services EN 15 038, issued by the European Committee for Standardization (2006). Quality issues have also been a recurring topic at audiovisual translation (AVT) conferences, but in AVT, practice levels of QA and QC appear to be subject to fluctuations, and AVT research into QA and QC, including revision, is quite limited. This article will first clarify a number of terminological issues, discuss some of the relevant literature on translation and revision quality parameters and procedures, and report on a detailed survey conducted in 2013 on QA and QC practices in the subtitling industry.
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 | 0.008 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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