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Record W2620874402 · doi:10.18778/2353-6098.3.10

Laying Bare: Agamben, Chandler, and The Responsibility to Protect

2015· article· en· W2620874402 on OpenAlexaff
Gabriel Quigley

Bibliographic record

VenueAnalyses/Rereadings/Theories A Journal Devoted to Literature Film and Theatre · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsResponsibility to protectSovereigntyTrespassLawPunishment (psychology)Human rightsPolitical scienceSociologyPhilosophyPoliticsPsychologySocial psychology

Abstract

fetched live from OpenAlex

This paper demonstrates the hidden similarities between Raymond Chandler’s prototypical noir The Big Sleep, and the United Nations Responsibility to Protect (R2P) document. By taking up the work of philosopher Giorgio Agamben, this paper shows that the bare life produces the form of protection embodied by Philip Marlowe in Chandler’s novel and by the United Nations Security Council in R2P. Agamben’s theorizing of the extra-legal status of the sovereign pertains to both texts, in which the protector exists outside of the law. Philip Marlowe, tasked with preventing the distribution of pornographic images, commits breaking-and-entering, withholding evidence, and murder. Analogously, R2P advocates for the Security Council’s ability to trespass laws that safeguard national sovereignty in order to prevent “bare” atrocities against human life. As Agamben demonstrates, the extra-legal position of the protector is made possible by “stripping bare” human life. This paper also gestures towards limitations of Agamben’s thought by indicating, through a comparison of these two texts, that bare life produces states of exception as the object of protection rather than punishment.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.016
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0100.042
Scholarly communication0.0100.011
Open science0.0010.005
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.305
Teacher spread0.256 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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