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Record W2754749450 · doi:10.1017/s0959774317000713

Disarticulate—Repurpose—Disrupt: Art/Archaeology

2017· article· en· W2754749450 on OpenAlexaboutno aff
Doug Bailey

Bibliographic record

VenueCambridge Archaeological Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsVisionNarrativeContext (archaeology)ColonialismPoliticsHistoryVisual artsArtAestheticsArchaeologySociologyAnthropologyLiteraturePolitical scienceLaw

Abstract

fetched live from OpenAlex

This project sees archaeology and art as a political tool for disrupting conventional, politically loaded narratives of the past. Rather than producing institutionally safe narratives conventionally certified as truth, archaeologists should follow the lead of artists who use the past as a source of materials to be reconfigured in new ways to help people see in new ways. Using as an example the works of the Canadian artist Ken Monkman, who subverts nineteenth- century landscape painting to reinsert the missing critiques of Anglo-American colonialism, dominance of nature, and heteronormativity, this paper advocates disarticulating materials from the past by severing them from their context, repurposing them to bring contemporary concerns to the fore and creating new, disruptive visions from them. The article proposes the practice of an art/archaeology.

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)0.004
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0180.070
Scholarly communication0.0160.007
Open science0.0010.010
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.045
GPT teacher head0.359
Teacher spread0.314 · 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
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

Citations21
Published2017
Admission routes1
Has abstractyes

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