Scholar

Representations of ‘Leftover Women’ in the Chinese English-language News Media

By: Yating Yu  

Single women who are older than twenty-seven have been labelled as ‘leftover women’ by the Chinese media since 2007. As Fincher (2014) argues, ‘The stigma surrounding “leftover” women intensifies pressure on women in their mid- to late twenties to rush into marriage with the wrong man’ (p.16). The scarcity of media studies from linguistic perspectives on the topic of leftover women, especially in the Chinese English-language news media, has provided a rationale for conducting this study. In order to fill this niche in the literature, this study investigates how leftover women are linguistically represented in the English-language news media in China by employing a corpus-assisted approach to critical discourse analysis. A specialised corpus of 303 English news articles (i.e., 236,254 words), covering the years between 2007 and 2017, was built for this purpose. Corpus linguistics techniques were employed to quantify the Meaning Shift Units (MSUs) of the lemma leftover women (Sinclair 1996, 2004) and van Leeuwen’s (2008) sociosemantic approach to social actors and actions was applied to inform the classification of MSUs in context. These findings shed light on media representations of leftover women, the contested ideologies emerging from these representations, and how shifting gender politics and identity shapes and are shaped by media in the world’s most populous nation.

LEFTOVER WOMEN; REPRESENTATIONS; CORPUS-ASSISTED APPROACH TO CRITICAL DISCOURSE ANALYSIS
Media Cultures
Paper Presentation in a Themed Session



Yating Yu

PhD Candidate, Department of English, The Hong Kong Polytechnic University, Hong Kong
Hong Kong

YU Yating is a PhD candidate from the Department of English, the Hong Kong Polytechnic University. Her research interests are in media studies, gender studies, corpus linguistics, (critical) discourse studies, and metaphor studies. Her recent publication was accepted by the journal Gender and Language.