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Frame diversity in Pakistani crime reality shows: a content analysis

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dc.contributor.author Sana Khaqan Malik
dc.date.accessioned 2020-10-23T07:32:11Z
dc.date.available 2020-10-23T07:32:11Z
dc.date.issued 2018
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/3788
dc.description Supervisor: Dr. Najma Sadiq en_US
dc.description.abstract Crime reality shows have been a common source of infotainment since the past few years. Sar-e-Aam and Khufia Operation were the most watched shows in the prime-time. This study has identified different frames applied by these crime reality shows to influence the audience. Types of crimes have been highlighted in this study that also reflect the problems in Pakistani context. Framing theory has been studied under the umbrella of content analysis of top rated shows. The content analysis established that corruption was a major crime highlighted by these crime shows and the dominant form of presentation was episodic in nature. Public shaming was the most important frame strongly used by these crime shows. Human interest frame was used to include the point of view of victims affected by crimes and offenders that committed them. Individualistic causal responsibility was identified to be framed and the solutions lied in punitive treatment responsibility. Animalistic, mechanistic and disease related metaphors were used to describe the traits of the offenders in context of dehumanization. Tertiary victimization was focused in the shows and was oriented towards the society being the victimized by crimes like corruption. Identity of victims and offenders was framed by giving their personal information. en_US
dc.language.iso en_US en_US
dc.publisher National University of Sciences and Technology Islamabad en_US
dc.subject crime reality shows, forms of presentation, attributions of causal and treatment responsibility, victimization, dehumanization, human interest, identity, victims, offenders, public shaming ii en_US
dc.title Frame diversity in Pakistani crime reality shows: a content analysis en_US
dc.type Thesis en_US


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