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Research Article

EEO. 2021; 20(4): 2719-2731


The Portrayal of Violence against Women in Pakistani Electronic Media

Sidra Amjad, Dr. Shahla Qasim, Dr. Urooj Fatima Alvi, Fakhra Amjad.




Abstract

The research aims at highlighting the violence against women that is portrayed by Pakistani electronic media. Recent studies have shown that the media portrays women as weak, subjugated deeply drowned in the patriarchal system. However, violence against women can take many forms such as domestic violence, rape, honor killing, etc. The research is qualitative in nature and the data type is secondary. The population includes different news related to the violence against women from different channels of Pakistani electronic media. The sample includes a total of four videos that depict how the media tends to portray violence against women. The research instrument employed in the current study is Lazar's feminist critical discourse analysis model of tabloidization (2014). The news highlighting the plight of violence against women is taken from various news channels i.e., GEO News, BOL News, City 42 News, and ARY News. The sampling procedure undertaken in this research is critical case sampling and the research design is cross-sectional. The data is analyzed on various levels i.e., lexical, syntactic, and paralinguistic level where Lazar's Model (2014) is applied to effectively evaluate how the media portrays violence against women. However, at the level of tabloidization, the suprasegmental features are considered in detail such as stress and intonation patterns of the news anchors while delivering the news regarding female gender-based violence. The results elucidate that the Pakistani media is extremely tabloid and tries to depict the women as weak, subjugated, suppressed, lacking freedom of movement, and prone to violence. Women are more prone to violence by men because of the patriarchal structure embedded in our society.

Key words: Critical Discourse Analysis, Feminist Critical Discourse Analysis, Tabloidization, suprasegmental features, Electronic Media, News






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