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The Aura of Againness

2017· book· en· W2758685990 on OpenAlexaff
Nico Dicecco

Bibliographic record

VenueOxford University Press eBooks · 2017
Typebook
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAuraMateriality (auditing)Adaptation (eye)Embodied cognitionContext (archaeology)Identification (biology)AestheticsCognitive scienceArtEpistemologyHistoryPsychologyPhilosophyNeuroscienceEcology

Abstract

fetched live from OpenAlex

Abstract By examining the complexities of aura, authenticity, materiality, and reception in the context of adaptation studies, Chapter 35 argues against the idea that adaptations are a specific kind of text and in favor of the idea that adaptations are actively constituted as such through performance: through live and embodied acts of identification that have significant material consequences. Drawing on several foundational concepts in adaptation studies and performance theory, Chapter 35 articulates a reception model of adaptation that is relevant not only to theatrical adaptations but across media and genres by showing the ways the aura of adaptation is generated as much through the unique spatiotemporal presence of an artwork as through its momentary disappearance from its place and time.

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)0.002
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.023
Scholarly communication0.0080.006
Open science0.0010.007
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0120.002

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 head0.040
GPT teacher head0.206
Teacher spread0.167 · 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
GenreOther

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

Citations13
Published2017
Admission routes1
Has abstractyes

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