Context, Field and Landscape of Audiovisual Translation in the Arab World
Bibliographic record
Abstract
Translation, as a cultural mediation, builds bridges between the Arab world and the outside world, particularly the west and continues to occupy a pivotal place in Arab society. Over the past two centuries, and since the establishment of the school of translation in Cairo in 1835, translation has been viewed as a vehicle of Nahda (progress) and Tanweer (enlightenment). Over the past two decades, however, translation in the Arab world has been radically transformed both at the practice and policy levels. The turn of the new millennium has brought about changes that have shaken the state of affairs and challenged old thinking and the ways of doing things. First, digital technology has changed the way things are done from work, play and study to the ways we socialise, shop and entertain ourselves. Second, a report on human development in the Arab world published in 2002 by the United Nations Development Programme (UNDP), revealed the unhealthy state of translation in most Arab countries. The paper examines the state of audiovisual study in Arabic and invites scholars to focus a lot more on their own local environment. It argues that a quarter of a century after the conference that launched the concept of AVT in Europe in 1995, the time has come for Arab academia to start developing its (own) theoretical frameworks for the localisation of audiovisual translation studies with the view of making translation studies not only relevant to society but also to play the role it was envisaged two centuries earlier.
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.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.026 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".