MétaCan
Menu
Back to cohort
Record W2326691886 · doi:10.3167/sa.2010.540206

Body Shock: The Political Aesthetics of Death

2010· article· en· W2326691886 on OpenAlexfundno aff
Uli Linke

Bibliographic record

VenueSocial Analysis · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
FundersCentral European UniversityUniversity of Toronto
KeywordsSpectacleEntertainmentAppealAestheticsSubjectivityPoliticsSociologyState (computer science)Political subjectivityLawMedia studiesPolitical scienceArtPhilosophy

Abstract

fetched live from OpenAlex

In a global media market, images of war and victimhood are trafficked as master tropes of trauma situations with immense emotional appeal. Concurrent with this transformation of historical atrocities into consumable commodities, new forms of spectatorship—focused on bodies, medicine, and death—are being produced by the entertainment industry. The article examines this fascination with corpses by focusing on Body Worlds, a traveling anatomical exhibit that was initially launched in Germany. I interrogate the means by which dissected corpses are presented as popular entertainment in a post-Holocaust society and seek to explain the installation's global appeal. My research reveals that the collusion between the state and private enterprise not only endorses the global traffic in corpses but also enables the public spectacle of anatomical human bodies by negating subjectivity, violence, and history.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.029
Scholarly communication0.0070.003
Open science0.0000.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.022
GPT teacher head0.350
Teacher spread0.328 · 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 designTheoretical or conceptual
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

Citations9
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSocial AnalysisSame topicGeographies of human-animal interactionsFrench-language works237,207