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Record W4236048906 · doi:10.1386/jcs.4.1.185_5

Book Reviews

2015· article· en· W4236048906 on OpenAlexaff
Chelsea Haines, Shauna Jean Doherty, John G. Hampton, Kelli Jerome, Charlotte Latham Kent, Nives Hajdin, Amber Christensen

Bibliographic record

VenueJournal of Curatorial Studies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsYork University
Fundersnot available
KeywordsExhibitionArt historyArtMedia studiesSociology

Abstract

fetched live from OpenAlex

Abstract Exhibition as Social Intervention: ‘Culture in Action’ 1993, Joshua Decter, Helmut Draxler and Others London: Afterall Books (2014), 224 pp., Paperback, ISBN: 978-3-86335-448-0, US$27.50 New Collecting: Exhibiting and Audiences After New Media art, Beryl Graham (ed.) Farnham, Surrey: Ashgate (2014), 234 pp., Hardcover, ISBN: 978-1-40944-894-5, E-book, ISBN: 978-1-40944-895-2, £60.00 Show Time: The 50 Most Influential Exhibitions of Contemporary art, Jens Hoffmann London: Thames and Hudson (2014), 256 pp., Hardcover, ISBN: 978-0-50023-911-7, £29.95 The Multisensory Museum: Cross-Disciplinary Perspectives on Touch, Sound, Smell, Memory and Space, Nina Levent and Alvaro Pascual-Leone (eds) Lanham, MD: Rowman and Littlefield (2014), 384 pp., Hardcover, ISBN: 978-0-75912-354-0, US$75.00 The Armory Show at 100: Modernism and Revolution, Marilyn Satin Kushner and Kimberly Orcutt (eds) London: D. Giles Limited (2013), 512 pp., Hardcover, ISBN: 978-1-90780-404-5, US$79.95 Curious Lessons in The Museum: The Pedagogic Potential of Artists’ Interventions, Claire Robins Farnham, Surrey: Ashgate (2013), 246 pp., Hardcover, ISBN: 978-1-40943-617-1, £65.00 Self-Organised, Stine Hebert and Anne Szefer Karlsen (eds) Bergen and London: Hordaland Centre and Open Editions (2013), 168 pp., Paperback, ISBN: 978-0-94900-417-8, £17.00

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.633
Threshold uncertainty score0.524

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0090.005
Open science0.0030.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.6330.563

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 head0.259
GPT teacher head0.345
Teacher spread0.086 · 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.

Study designNot applicable
Domainnot available
GenreReview

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
Published2015
Admission routes1
Has abstractyes

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