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The poetics of Libretti: reading the opera works of Gwen Harwood and Larry Sitsky.

Gwen Harwood is one of Australia’s most celebrated poets. Her longstanding collaboration with composer Larry Sitsky produced six substantial operas between 1963 and 1982; Fall of the House of Usher (1965); Lenz (1970); Fiery Tales (1975, based on Chaucer’s Canterbury Tales and excerpts from Boccaccio’s Decameron); Voices in Limbo (1977); The Golem (1980, first performed in 1993); and De Profundis (1982, a setting of Oscar Wilde’s letters). Both Harwood and her critics acknowledge the libretti as some of her best writing (Harwood cites her libretto for Lenz as her ‘selected poem’); to date, there has been no major study of these works. This thesis engages with Harwood’s opera texts, arguing for readings that are neither atomist nor reductive but jointly focused on both the effect of the text and the mechanics of its production. It begins by outlining the theoretical terrain of words and music studies and establishes an approach to Harwood and Sitsky’s operas based on the idea that opera’s textual exaggeration is a function of its multiple critical components; that is, the intersection of words and music, collaborative authorship, and dramatic language. The thesis then offers focused studies of each of these aspects in Harwood and Sitsky’s works, constructing a literary picture of the opera texts. Primary sources include the scores of the operas (usually copies of the composer’s autograph), selected correspondence between Sitsky and Harwood, drafts and typescripts of the libretti (held in the National Library, Canberra, and the Fryer Library, University of Queensland), and selected essays by Harwood on her words for music. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1331575 / Thesis (M.A.) -- University of Adelaide, School of Humanities, 2008

Identiferoai:union.ndltd.org:ADTP/264548
Date January 2008
CreatorsWood, Alison J.E.
Source SetsAustraliasian Digital Theses Program
Detected LanguageEnglish

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