The Study of Localization in the Persian Version of News Websites: A CDA perspective
Bibliographic record
Abstract
The present study is aimed to shed light on the steps taken by translators at Euronews website in translating the News into Persian for the localized version of the website. Intending to do a Critical Discourse Analysis (CDA) on the findings of the comparison of the website localization project, the researcher chose the highly visited website from the news genre, namely Euronews, which is supposed to bear ideological load. To achieve the objective, the original and localized versions of the website was probed in inconsecutive days, within this period, the news on the English and Persian websites, having the same textual content, and containing some ideological implications in their translations, were investigated. The textual differences between the original and localized versions of the website were extracted and analyzed critically based on Farahzad‟s (2011) three dimensional CDA model and Newmark‟s (1988) classification of translation procedures. Also, the semiotic aspect, that is the graphics on the relative web pages, was investigated. These were done to examine the ideological implications of the differences and to reach conclusions on the ideologically significant translational attempts in Euronews website and in news website localization projects in general. At the end it was concluded that the translators have removed or added, expanded or narrowed down and most frequently changed the ideas stated in the original version. The purpose of this was to convey their own ideologies and stances, or those of the website owners‟ and news agencies, to visitors.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".