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Record W2912409771 · doi:10.5040/9781350985636.ch-004

Sex, Art and Museums: On the Changing Institutional Censorship of Shunga

2018· book-chapter· en· W2912409771 on OpenAlexaboutno aff
Louise Boyd

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCensorshipArtSociologyVisual artsPolitical scienceLaw

Abstract

fetched live from OpenAlex

rt is continuously subjected to insidious forms of censorship. This may be by the Church to guard against moral degeneration, by the State to promote a specific political agenda or by the art market, to elevate one artist above another. Now, and in the last century, artwork that touches on ethnic, religious, sexual, national or institutional sensitivities is liable to be destroyed or hidden away, ignored or side-lined. Drawing from new research into historical and contemporary case-studies, Censoring Art: Silencing the Artwork provides diverse ways of understanding the purpose and mechanisms of art censorship across distinct geopolitical and cultural contexts from Iran, Japan, and Uzbekistan to Britain, Ireland, Canada, Macedonia, Soviet Russia, and Cyprus. Its contributions uncover the impact of this silent control of the production and exhibition of art and consider how censorship has affected art practice and public perceptions of artworks.

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)0.001
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: none
Teacher disagreement score0.009
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.015
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.056
GPT teacher head0.289
Teacher spread0.233 · 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
Published2018
Admission routes1
Has abstractyes

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