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Record W2990012520 · doi:10.4324/9781315668505-27

‘The trophies of their wars’

2018· book-chapter· en· W2990012520 on OpenAlexaboutno aff
Sara Matthews

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInterdisciplinary Cultural and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

This chapter explores the concept of the war trophy in relation to two exhibits at the Canadian War Museum: a black Mercedes-Benz bulletproof limousine that was once used by Hitler as a parade car and Gertrude Kearns&s; painting Somalia Without Conscience. It examines free association as a method of cultural analysis that can attend to the affective force of the social encounter. The chapter explains a fictive exhibit that brings the car into conversation with the painting and considers how the embodied subjects of war are constructed in the presence of memorial space. It focuses on how visitor responses to the car and the painting open new questions with regard to the mandate of the museum to remember, to preserve and to educate. The chapter suggests an imaginary exhibit that brings the car into juxtaposition with the painting. The painting provokes many questions but ultimately the responsibility for answers lies with the viewer.

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 score0.090
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.020
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0190.002

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 head0.040
GPT teacher head0.299
Teacher spread0.259 · 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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