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Record W3186756989 · doi:10.22215/etd/2021-14523

Restart the ‘World’ with Revolutionary Ruptures: Imagining Identity through War & in Crisis – Apocalyptic Rhetoric & the American Civil Religion

2021· dissertation· en· W3186756989 on OpenAlexaff
Sarah Sharp

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsRhetoricMythologyTragedy (event)Identity (music)NarrativeState (computer science)Identity crisisThe ImaginarySpanish Civil WarValue (mathematics)AestheticsSociologyPolitical scienceLawHistoryLiteratureArtSocial sciencePsychoanalysisPhilosophyPsychologyTheology

Abstract

fetched live from OpenAlex

The response to 9/11 involved appealing to apocalyptic rhetoric to capitalize on the affective chaos following the tragedy to discursively mobilize actors while engaging in historical (re)imagining of the state. This thesis uses Benedict Anderson's concept of Imagined Communities as it concerns national/historical-time to expand upon Paul Fussell and Lilie Chouliaraki's work on the War Imaginary. It demonstrates how the operative value of myth mirrors and is serviceable to the discursive-reconstitution of the state in times of crisis and how individual self-understanding emerges via Narrative Identity. The major mythic structures that provide the source of authority to American self-understanding include: the American civil religion and the American culture-wars. Crisis compels identification to make sense of unfamiliar events according to one's origin myth; adaptive 'editing' for familiarity permits those in-crisis to shape/eliminate anything that contradicts their moral-truth to consolidate it as 'authentic' when faced with the 'inauthentic' threat of an alternative.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.620
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.308
Teacher spread0.270 · 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 teacher head, not a consensus.

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
Published2021
Admission routes1
Has abstractyes

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