Schäffner, Christina and Bassnett, Susan (eds). 2010. Political Discourse, Media and Translation. Newcastle upon Tyne: Cambridge Scholars Publishing. (Book Review)
Notice bibliographique
Résumé
Are we well informed?This is the (provocative) question that one might raise after reading this volume, a collection of articles tackling the notion of recontextualization in news translation, with a special focus on political discourse.The book, which provides some answers to the intricate relationship between translation and media, investigates the complex (and most often invisible) work of news translators.Journalists, as well as media in general, play the crucial role of mediators between institutions, their representatives and the public.Our knowledge of governmental activities, political communications, public addresses, etc., entirely depends on media.When translating some news in order to report from foreign countries, journalists filter, select, add, omit and adapt information, which contributes to releasing some localized news version for the new target audience.In brief, they recontextualize it.But, one might wonder, are they really conscious of their power, their agency, the consequences, effects and impact that such manipulations of the information can have on the public?Although, on the one hand, journalists tailor the way we come to grips with a culture, hardly ever are they trained as translators, and as a consequence, they perform their task without bearing in mind some of the traditional concerns of Translation Studies (TS).One such concern is the issue of fidelity between source and target texts.Who, then, dictates the rules of the(ir) game?One could argue that newspapers and TV political orientations, as well as advertising investors' economic interests-to name a few-do indeed influence news translation.However, they are just the tip of the iceberg of a (much wider) manipulative process.The reasons for such transformations, and the way recontextualization and/or localization are carried out, perhaps, are more intricate than it might initially seem, and may be grounded in arbitrary decisions: namely, decisions made by those who select the information to be translated from the very start on the basis of specific, yet subjective, strategies.But, what are these strategies or techniques?Who revises the 'final product'?How does reception influence decision-making?Why are articles seldom labeled as translations?Why do journalists rarely define themselves as translators?Political Discourse, Media and Translation is the printed outcome of a symposium held in February 2007 at Aston University.The collected papers shed light on the above questions in a somewhat provocative fashion intellectually speaking.Their overall goal is not to cast doubt on or assess the profession of journalists as translators, but to demonstrate that the principle of equivalence applied to news translation does not serve TranscUlturAl, vol.5.1-2 (2013), 219-226 http://ejournals.library.ualberta.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,005 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,008 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,040 | 0,035 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».