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Record W894879677

Brett Josef Grubisic, Gisele M. Baxter, and Tara Lee, Eds. Blast, Corrupt, Dismantle, Erase: Contemporary North American Dystopian Literature

2014· article· en· W894879677 on OpenAlexvenueaboutno aff
Brent Ryan Bellamy

Bibliographic record

VenueEnglish studies in Canada · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsDystopiaUtopiaWonderHistoryIronyDefamiliarizationLiteratureArt historyAestheticsMedia studiesSociologyArtPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Brett Josef Grubisic, Gisele M. Baxter, and Tara Lee, eds. Blast, Corrupt, Dismantle, Erase: Contemporary North American Dystopian Literature. Waterloo: Wilfred Laurier UP, 2014. 480 pp. Frack, Gene-splice, Hinder, Immolate ... We all have dystopias to write. With an introduction and twenty-five separate essays, Blast, Corrupt, Dismantle, Erase covers impressive ground. The book comes to terms with a genre that appears to be, if anything, broadly conceived: while the sheer length of the project suggests that it might have benefited from editorial discretion, the ethos of dystopia lends itself to varied applications and interpretations. Indeed, the rewards of engaging the text as a whole are great, especially as some of the strongest work is found in its latter half. The collection, when read in sequence, does not allow one to settle in to a particular geography, national-economic space, or version of dystopia; instead, the arrangement of the chapters jumps, for instance, from alter-histories of women in the Mexican Revolution, to the deeply troubled Montreal of the mid-nineties, to Douglas Coupland's slacker realism. The effect produced is one of cycling defamiliarization, a shuffling of imagined destinies and short-circuited hopes that comprise a dauntingly heterogeneous futurity. These vertiginous snap between futures subtends, but does not override, the critical intervention of the book: to shift contemporary studies of dystopia from an Anglo-American or loosely international frame to one that understands the dystopian literary mode, and the texts specifically produced, in the wake of the cultural changes that have taken place in North America since the North American Free Trade Agreement (nafta). In this collection, held separate from its literary tradition, dystopia becomes a critical tool that assesses the unevenness of the North American political economy. Indeed, the dizziness of considering, in turn, Nalo Hopkinson's hollowed Toronto, Alex Rivera's sleep factories, and Neil Gaiman's dystopian phantasmagoria emulates the free flow of goods across Canadian, U.S., Mexican, and the ever-obfuscated Indigenous borders of the continent. From the start, I noticed a typical formal split in the author's approaches to dystopia. On the one hand, some seem to refuse to assume the kind of shared intimacy with their object literary critics so often accept as a part of their endeavour. This variety of essay in the collection relies heavily on quotation, communicating as much as possible of the dystopia in question in its own words, be it Cormac McCarthy's futureless future or Lisa Robertson's critique of a gentrified Vancouver. I like this approach particularly in 'The Dystopia of the Obsolete': Lisa Robertson's Vancouver and the Poetics of Nostalgia, Paul Stephens's essay on Robertson's The Office for Soft Architecture (2003), precisely because he seemed able to remain true to her poetics and her politics through his citational practice. On the other hand, Sharlee Reimer insists on the critical project of interpretation championed by Larissa Lai's Salt Fish Girl (2002) in Logical Gaps and Capitalist Seduction in Larissa Lai's Salt Fish Girl; Sharon DeGraw places Hopkinson's Brown Girl in the Ring (1998) against Detroit's deterioration to highlight the green urban policy of the novel; while Robert T. Tally Jr. comes closest to naming the obfuscated futurity of the global hegemon through Gaiman's American Gods (2001) in Lost in Grand Central: Dystopia and Transgression in Neil Gaiman's American Gods. …

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.221
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2014
Admission routes2
Has abstractyes

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