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Record W7138850240 · doi:10.14288/canlit.vi262.198926

The Mad, Queer Time and Space of bill bissett’s lunarian Narratives

2023· article· en· W7138850240 on OpenAlexaffabout
Drew McEwan

Bibliographic record

VenueOpen Collections · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicReligious Studies and Spiritual Practices
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTemporalityQueerPoetryNarrativeNormativePerformativitySpace (punctuation)Perspective (graphical)Queer theory

Abstract

fetched live from OpenAlex

Since 2001, Canadian poet, artist, and performer bill bissett has, in public statements and interviews, and in his poetry and art, explored the faraway planet of lunaria as his autobiographical origin. In 2001, bissett published the ambitious work lunaria, a book-length poem in which a speaker recounts their origin on lunaria and desire to return, as well as providing an account of the lunarian ways of life, geographies, relationships, and lifecycles. This article by Drew McEwan explores the mythical planet both in lunaria and in the lunarian autobiographical paratexts as critical developments in bissett’s work and ideas. Further, it argues that these texts articulate a mad and queer temporality that provides a critical perspective on normative “erthling wayze.” bissett’s poetic and extra-poetic lunarian texts elaborate a utopian state of temporality, community, and nurturance borne in relation to the failures of those deemed too crazy, too queer, here on Earth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.288
Threshold uncertainty score0.573

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0270.042
Scholarly communication0.0100.006
Open science0.0010.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.271
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2023
Admission routes2
Has abstractyes

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