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Record W3146794504

In the Modern Age

2014· book· en· W3146794504 on OpenAlexaboutno aff
David Howes

Bibliographic record

VenueBloomsbury Academic eBooks · 2014
Typebook
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsArt historyThe artsMetropolitan areaSociologyArtPerceptionVisual artsMedia studiesAestheticsHistoryPsychology
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Make it New! - Reforming the Senses David Howes (Concordia University, Canada) 1. The Social Life of the Senses: Ordering and Disordering the Modern Sensorium Tim Edensor (Manchester Metropolitan University, UK) 2. Urban Sensations: A Retrospective of Multisensory Drift Alex Rhys-Taylor (Goldsmiths University, UK) 3. The Senses in the Marketplace: Commercial Aesthetics for a Suburban Age Adam Mack (School of the Art Institute of Chicago, USA) 4. The Senses in Religion: Pluralism, Technology and Change Isaac A. Weiner (Ohio State University, USA) 5. The Senses in Philosophy and Science: From Sensation to Computation Mathew Nudds (University of Warwick, UK) 6. Medicine and the Senses: Bodies, Technologies and the Empowerment of the Patient Anamaria Iosif Ross (independent scholar) 7. The Senses in Literature: From the Modernist Shock of Sensation to Postcolonial and Virtual Voices Ralf Hertel (University of Hamburg, Germany) 8. Art and the Senses: The Avant-Garde Challenge to the Visual Arts Hannah Higgins (University of Illinois Chicago, USA) 9. Sensory Media: Virtual Worlds and the Training of Perception Michael Bull (University of Sussex, UK) Notes Bibliography Notes on contributors Index

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)0.001
metaresearch head score (Gemma)0.002
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 score0.040
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0060.013
Scholarly communication0.0090.009
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0400.010

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 head0.046
GPT teacher head0.250
Teacher spread0.204 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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