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Record W4391105920 · doi:10.4324/9781003398639-5

Bunker media

2024· book-chapter· en· W4391105920 on OpenAlexaboutno aff
Greg Elmer, Stephen J. Neville

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsnot available
Fundersnot available
KeywordsBunkerEnvironmental scienceGeographyArchaeology

Abstract

fetched live from OpenAlex

Unlike the previous chapters, this chapter argues that the cold war bunker represented a globalized media scarce condition, where populations were encouraged to seek shelter underground. Yet while the bunker mirrored the media scarce conditions of many other communities discussed in our book, it was initially sold as an extension of the family home, replete with the creature comforts of the time – notably consumer media technologies. However, the chapter details how this mythic media abundant bunker gave way to militarized bunker visions that emphasized the installation’s redundant qualities. Not only would the state bunker contain layers of redundant media technologies in case of attack or technological failure, but the cold war bunker would also never be used for its intended purpose of protection against nuclear arms. Focusing on the case of the Canadian “continuity of government” bunker located outside of the national capital Ottawa, the chapter concludes with an analysis of the contemporary return of the media abundant bunker, or bunker media, an event hall and Cold War Museum that once again attempts to keep the precarity of its apocalyptic media scarcity at bay. Instead of nuclear annihilation, the newly refashioned bunker turns to zombies and spy games to remediate and placate the existential cold war threats of an uncertain future in and beyond the underground.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.154
Threshold uncertainty score0.514

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1540.037

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 head0.034
GPT teacher head0.294
Teacher spread0.260 · 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
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
Published2024
Admission routes1
Has abstractyes

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