From the Dutch corantos to Convergence Journalism: The Role of Translation in News Production
Bibliographic record
Abstract
This article provides a overview of the role translation has played in news transmission since the birth of journalism until the 21st century. The paper focuses on three periods and the ways in which translation has been present in news production: (1) translation at the origin of newspapers in 17th- and 18th-century Europe, with particular reference to England, Spain and Scandinavia, where translation was, in fact, the staple diet of the first pamphlets published in those countries, (2) from the late 19th century onwards, the interplay between language and translation has also been present in the activity of foreign correspondents, albeit often in a very invisible manner, and (3) as the journalistic activity was professionalized, the importance of translation can be traced in the need for journalists to be trained in foreign languages as well as in the appearance of news agencies whose activity is to a great extent translational. Finally, the advent and spread of the Internet has made the role of translation more apparent, even if it remains an invisible second-rate activity within the news production process.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.030 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".