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Record W4386693107 · doi:10.5040/9781350386006.ch-007

War Art, Official and Unofficial

2023· other· en· W4386693107 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHistoryAncient history

Abstract

fetched live from OpenAlex

What exactly is contemporary war art today? Edited by Kit Messham-Muir, Uroš Čvoro and Monika Lukowska-Appel, Art in Conflict: The Politics of Artists in War Zones brings together chapters from leading international contemporary artists, theorists and curators, plus the voices of contemporary war artists through original edited interviews. Art in Conflict focuses on three overlapping themes dominating current western war art: firstly, the role of memory and amnesia in colonial contexts; secondly, the complex role of ‘official’ war art, a subgenre of contemporary war art peculiar to Australia, Canada and the UK, each with a century-long evolving tradition of official war art; and thirdly, questions of testimony and knowing in relation to alleged war crimes, torture and genocide. A strong undercurrent throughout Art in Conflict is western colonialism and military intervention, both historically and within living memory. This is particularly relevant to the Anglophone world, currently subject to the overdue widescale critique of violent Western colonising and re-colonising. Many chapters and interviews address the impact of British colonising in Australia, India and its relation to historical conflicts, and more recent expeditionary ventures with the US’s War on Terror. Art in Conflict includes chapters from leading contemporary artists, theorists and curators, Ana Carden-Coyne, Charles Green, Anthea Gunn and Laura Webster, Paul Lowe, Lisa Slade, Kit Messham-Muir and Uroš Čvoro, who discuss the war art of Tony Albert, Khadim Ali, John Akomfrah, Derek Eland, Lana Čmajčanin, Indigenous Australian Aṉangu artists, Gertrude Kearns, Mladen Miljanović, Michael Zavros and others. Uniquely, this book features three substantial interview chapters drawn from hours of conversation with some of the world’s leading contemporary practitioners and experts, including Abdul Abdullah, Alana Hunt, eX de Medici, (Australia), David Cotterrell, Andrew Sneddon (UK), Baptist Coelho (India), Todd Stone (US), Karen Bailey and Phillip Cheung (Canada), as well as eminent war historian Prof Joanna Bourke (Birkbeck, London).

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.008
Scholarly communication0.0160.006
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0150.002

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 head0.024
GPT teacher head0.248
Teacher spread0.224 · 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
Published2023
Admission routes1
Has abstractyes

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