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Record W2762587891 · doi:10.1080/13576275.2017.1377167

Birth, death and survival: sources of political renewal in the work of Hannah Arendt and Virgil’s<i>Aeneid</i>

2017· article· en· W2762587891 on OpenAlexaff
Catherine Frost

Bibliographic record

VenueMortality · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHannah Arendt's Political Philosophy
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPoliticsElement (criminal law)PhilosophyAction (physics)SacrificeSociologyMythologyPsychoanalysisLawEpistemologyPolitical scienceTheologyPsychology

Abstract

fetched live from OpenAlex

Does death provide a generative force in politics? The great theorist of political founding, Hannah Arendt, insisted that birth, not death, equipped us for the task of beginning, and pointed to Virgil’s Aeneid as a work that best understood this process. But the Aeneid is a work primarily concerned with sacrifice, suffering and death, and it highlights the losses that must be endured, the disorientation to be overcome, before renewal arrives. Reconsidering Arendt’s emphasis on action in the light of the themes of loss and despair in the Aeneid suggests that death cannot be definitively excluded from an Arendtian approach. Indeed, this element may lie close to the heart of her thinking. Virgil’s emphasis on the management of despair through prophecy suggests one reason Arendt might forego an emphasis on death, since accounts of founding, be they myth or theory, must first and foremost serve the needs of survival.

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)0.008
metaresearch head score (Gemma)0.009
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 score0.015
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.067
Scholarly communication0.0090.007
Open science0.0010.005
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0020.000

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 head0.090
GPT teacher head0.368
Teacher spread0.278 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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