首页> 外文期刊>Critical Discourse Studies >Acceptable bias? Using corpus linguistics methods with critical discourse analysis
【24h】

Acceptable bias? Using corpus linguistics methods with critical discourse analysis

机译:可以接受的偏见?使用语料库语言学方法与批判性话语分析

获取原文
获取原文并翻译 | 示例
       

摘要

This paper considers the proposal that corpus linguistics approaches can improve the objectivity of critical discourse analysis research, resulting in a more robust and valid set of findings. Taking a recent project which examined the representation of Islam and Muslims in the British press, corpus-driven procedures identified that Muslims tended to be linked to the concept of extreme belief much more than moderate or strong belief. There were differences across newspapers, with 1 in 8 Muslims describing it as extreme in The People while this figure was 1 in 35 for The Guardian. Such patterns of quantification, however, still require researchers to carry out their own critical interpretations with regard to what counts as acceptable frequencies.View full textDownload full textKeywordscorpus linguistics, Islam, bias, extremism, CDARelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/17405904.2012.688297
机译:本文考虑了语料库语言学方法可以提高批判性话语分析研究的客观性的建议,从而得出更为健壮和有效的结论。在最近的一项研究中考察了英国媒体中伊斯兰教和穆斯林的代表性的情况下,语料库驱动的程序确定,穆斯林倾向于与极端信仰概念联系在一起,而不仅仅是中度或强烈信仰。报纸之间存在差异,在《人民报》中有八分之一的穆斯林描述为极端,而在《卫报》中这一数字是三十分之一。然而,这种量化模式仍然需要研究人员对可以算作可接受的频率做出自己的批判性解释。查看全文下载全文关键词语言,伊斯兰教,偏见,极端主义,CDARelated var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,services_compact:“ citeulike,netvibes,twitter,technorati,可口,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/17405904.2012.688297

著录项

  • 来源
    《Critical Discourse Studies》 |2012年第3期|p.247-256|共10页
  • 作者

    Paul Bakera*;

  • 作者单位
  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 00:48:32

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号