Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.792012
Title: Stereotyping and translation in Arabic and English news texts with reference to Islamophobia and the Arab-Israeli conflict
Author: Askari, Shifa
ISNI:       0000 0004 8504 6218
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2019
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
Stereotyping, as defined in this thesis, is the use of generalization or shorthand for describing groups of people, cultures, religions or ethnicities. Stereotypes are to be distinguished from ideologies, which, as defined in this thesis, are sets of attitudes that manage social and political interests including the media. Ideologies work to serve particular interests by setting agendas and managing people's opinions to serve the ultimate goal of the ruling class. Stereotypical images can be used to serve certain ideologies especially when this is done systematically and in an organised manner. Technological advances, and especially the internet, have increased the volume of language and media exchange, hence increasing the translation of news texts. This research is concerned with tracking the role of translation in rendering stereotypical and ideological expressions between English and Arabic in relation to news texts extracted from two news services: BBC and Reuters. The general theory adopted is critical discourse analysis. The news texts are pertinent to two topics: the Israel/Palestine question and Islamophobia. The data is collected over one month: May 2016. The methodology followed for the purpose of analysis is the Discourse Historical Approach developed by Ruth Wodak et al. The methodology identifies a number of strategies which can be used to identify evaluative/stereotypical presentations in news texts: nomination, predication, perspectivation, mitigation and argumentation. It tries to incorporate as much relevant available knowledge as possible about the historical sources and the background of the social and political context in which discursive practices are embedded. The selected texts are analysed using the above methodology. Background information is gathered as part of the methodological approach. The analysis is followed by a comparative qualitative analysis of both the English and Arabic texts. A quantitative analysis is also conducted, by assigning numerical categories to the stereotypes/ideologies defined within the texts. Here, two types of stereotypes/ideologies are identified: those of the news service, and those of the likely reader. News service stereotypes/ideologies are identified through analysis of the relevant aspects of the text. Likely reader stereotypes/ideologies are identified where possible by determining the 'typical' or 'average' reader through extrapolation from statistically reliable quantitative publicly available sources, such as public opinion surveys conducted in America, Britain and the Arab world. The quantitative results are analysed, and then those for news service stereotypes/ideologies are compared to the qualitative analysis to provide a composite qualitative-quantitative analysis of each text. The results endorse the view that images of Islam in Islamophobia-related texts are generally negative for both English and Arabic texts, but more negative for English ones. For Sunni Islam, the stereotypes are consistently very negative. For Shia Islam the stereotypes vary between fairly and very negative for both English and Arabic texts. For the Israel/Palestine texts, the ideological and stereotypical expressions in the English texts are more pro-Israel than those in the Arabic ones. This research demonstrates that stereotypes are used in media to enhance the ideological agenda of the news service. It also shows that media contributes to developing new stereotypes.
Supervisor: Dickins, James Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.792012  DOI: Not available
Share: