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Record W2512159511 · doi:10.3138/tric.37.1.27

Around the Backside: Productive Disbelief in <i>Burning Vision</i>

2016· article· en· W2512159511 on OpenAlexvenueaboutno aff
Alana Fletcher

Bibliographic record

VenueTheatre Research in Canada · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicPoetry Analysis and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsTemporalityConversationMateriality (auditing)AestheticsConfusionIllusionSociologyAlienationHeterotopia (medicine)EpistemologyContingencyPhenomenology (philosophy)Visual artsPsychoanalysisPsychologyPhilosophyArtCommunicationCognitive psychologyLaw

Abstract

fetched live from OpenAlex

The work of Vancouver-based Métis playwright Marie Clements has often been commended for its emphasis on the connections that inhere among people and places, times and spaces. The time-space conversations of Burning Vision, one of the most spatially and temporally diverse of Clements’s works, have thus far been explained in terms of their ecological and indigenizing effects. While revelations of connectivity and windows opened onto alternate conceptions of spatio-temporality are significant results of the intercultural moments where Clements brings discrete times and places into conversation, it is also useful to acknowledge another, more immediate result of such dialogues: audience confusion, alienation, and disbelief. Such confusion points to a significant but as-yet unaddressed aspect of the Burning Vision: the way the play’s materiality works against its fiction, impeding audience immersion in the story unfolded. This article draws out this conflict through a phenomenological approach that illuminates how the refusal of the work’s material reality to disappear behind its fiction—to slip around the backside of the frontside illusion—prompts a productive kind of disbelief that structurally underlines the work’s arguments for interconnectedness.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.318
Teacher spread0.255 · 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.

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

Citations1
Published2016
Admission routes2
Has abstractyes

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