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“Restless Ecstasy”: Addiction, Reiteration, and Mediality in Klaus Knoesel’s Rave Macbeth

  • Maurizio Calbi
Part of the Reproducing Shakespeare: New Studies in Adaptation and Appropriation book series (RESH)

Abstract

Like Fodor’s Hamlet, Klaus Knoesel’s Rave Macbeth (2001), the very first feature-length film to be shot on a Sony’s 24P-1080 digital camera, resituates Shakespeare in the context of contemporary urban youth culture.1 It makes Shakespeare’s Macbeth inhabit the realm of rave culture, a nocturnal culture that finds its expression in a nameless rave club, and that re-marks the play as essentially a tragedy of the “thick night” (1.5.49). In the film the obsessive reiteration of music and the incessant bodily movements of 14,000 dance ravers combine with the repeated ingestion of hallucinogenic and addictive substances such as ecstasy—the film’s transposition of the “insane root/That takes the reason prisoner” (1.3.82-83) and/or its update of the “vap’rous drop … distilled by magic sleights” (3.5. 24; 26).2 Thus, as Douglas Lanier more generally argues in relation to products of popular culture he dubs “Shakespop,” the film selects aspects of Macbeth that resonate with pop culture—in particular the play’s rich array of “metaphysical” (1.5.28) substances—and re-activates and extends their meanings (Shakespeare 97).3 Moreover, Rave Macbeth is a highly self-reflexive film, drawing attention to multiple forms of (bodily) reiterations that often allegorize the film’s own status as a multifaceted reiteration and remediation of a Shakespearean story in mass media culture. Part of its self-reflexivity has to do with a male character named Hecate, chief drug dealer and media savvy who, unlike many other filmic versions of Macbeth, plays a prominent role and can indeed be seen as “the close contriver of all harms” (3.5.7).4

Keywords

Security Guard Music Video Addictive Substance Drug Scene Dance Floor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Maurizio Calbi 2013

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  • Maurizio Calbi

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