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Record W4389155142 · doi:10.1017/9781108560740.020

The Bomb

2023· book-chapter· en· W4389155142 on OpenAlexaff
Ann Larabee

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCriticismNuclear weaponManhattan projectObject (grammar)ConversationNuclear fissionAtomic energyLiteratureHistoryArt historyArtPhilosophyFissionPolitical scienceLawPhysicsEpistemologyNuclear physicsNeutronLinguisticsAgency (philosophy)

Abstract

fetched live from OpenAlex

This chapter focuses on the atomic bomb as imagined, debated, and dissected in the fiction and criticism of the twentieth century. Long before its invention in the Manhattan Project, atomic fission was an obsessive object of speculation in fiction by writers such as H. G. Wells, Talbot Mundy, and Olaf Stapledon. Rejecting the notion that research was directed simply toward the development of clean sources of energy, such writers steered the public conversation toward the apocalyptic consequences of the employment of nuclear physics in the development of arms. Larabee focuses on how the threat of nuclear apocalypse impacted literary criticism’s sense of its social mission. Although she reads the movement known as “nuclear criticism” as a failure, she reads John Adams’s and Peter Sellars’s opera Doctor Atomic as exemplary of “new critical and creative forms” that might “bring the humanities and sciences together to address threats such as nuclear weapons.”

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.078
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0040.004
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0780.027

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 head0.037
GPT teacher head0.240
Teacher spread0.203 · 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 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
Published2023
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicNuclear Issues and DefenseFrench-language works237,207