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    Drama and its political situations 1642-1660

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    This thesis aims to challenge the accounts of Interregnum drama which see it as either a void between the two "great" theatres of the Renaissance and Restoration, or as a period during which drama was written and published by "cavaliers." The thesis contends that because Interregnum drama reflects new conditions of production, it requires that we expand our idea of the generic limits of drama. By contemporary definitions there were a number of dramatic genres published, ranging from short pamphlet plays, skits, and dialogues to ten-act tragicomedies; and operas and shows were performed in the 1650s. Moreover, this drama was politicised because of the bans on performance. Therefore, moving between elite, and popular spheres, drama both registered and helped form readers' understanding of the Civil War crises from a range of political perspectives, which, in themselves, enable us to break down the notion of the Interregnum as only a binary struggle between "king" and "parliament." Methodologically, the thesis is historicist in the sense that it attempts to situate dramatic texts from 1642-1660 in political discursive and social contexts. In stressing the need to reinterpret the political position (and function) of dramatic texts it approaches the political situations of drama by examining emerging genres, analysing the circumstances of particular published and performed plays, and by investigating the careers of dramatists and groups of dramatists. The thesis is arranged in four sections in chronological order: Printed and Pamphlet Drama, Gender and Drama, Performed Drama, Genre and Politics. By reassessing the position of such diverse genres as pamphlet dialogues, performed opera, tragicomedies and plays by aristocratic women the thesis moves towads a reassessment of the place of Interregnum drama as a literary-political discourse with implications for the understanding of both Renaissance and Restoration drama, as well as that of the period 1642-1660

    Information Retrieval Model using Uncertain Confidence's Network

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