MétaCan
Menu
Back to cohort
Record W3010314560 · doi:10.1515/9783110664416

The Second World War in the Twenty-First-Century Museum

2020· book· en· W3010314560 on OpenAlexfundno aff
Stephan Jaeger

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsExhibitionNarrativeWorld War IIEmpathyReading (process)HistoryThe HolocaustVisual artsCultural memoryMedia studiesSociologyArt historyPsychologyArtLiteratureAnthropologyPolitical scienceLawArchaeologySocial psychology

Abstract

fetched live from OpenAlex

The Second World War is omnipresent in contemporary memory debates. As the war fades from living memory, this study is the first to systematically analyze how Second World War museums allow prototypical visitors to comprehend and experience the past. It analyzes twelve permanent exhibitions in Europe and North America – including the Bundeswehr Military History Museum in Dresden, the Museum of the Second World War in Gdańsk, the House of European History in Brussels, the Imperial War Museums in London and Manchester, and the National WWII Museum in New Orleans – in order to show how museums reflect and shape cultural memory, as well as their cognitive, ethical, emotional, and aesthetic potential and effects. This includes a discussion of representations of events such as the Holocaust and air warfare. In relation to narrative, memory, and experience, the study develops the concept of experientiality (on a sliding scale between mimetic and structural forms), which provides a new textual-spatial method for reading exhibitions and understanding the experiences of historical individuals and collectives. It is supplemented by concepts like transnational memory, empathy, and encouraging critical thinking through difficult knowledge.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.428
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0360.001

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 head0.028
GPT teacher head0.206
Teacher spread0.178 · 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; both teacher heads agree on what is shown here.

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

Citations31
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicMuseums and Cultural HeritageFrench-language works237,207