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Record W2135831753 · doi:10.3138/cras.41.3.342

Running Out of Gas: The Energy Crisis in 1970s Suburban Narratives

2011· article· en· W2135831753 on OpenAlexvenueno aff
Christian B. Long

Bibliographic record

VenueCanadian Review of American Studies · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyObsolescenceNarrativeUrban sprawlSuburbanizationAestheticsEnergy (signal processing)FiguringHistorySociologyPolitical economyPolitical scienceCivil engineeringLawBusinessArtLiteratureEngineeringPoliticsUrban planningArchaeology

Abstract

fetched live from OpenAlex

Abstract: In Back to the Future 1 and Part II, The Ice Storm, and The Virgin Suicides the negative effects of suburbanization are written onto the nature it purports to provide its residents. The cultural and economic logic of sprawl generates a built environment that accelerates the energy-crisis apocalypse tasted during the 1973 energy crisis. The paradoxes of suburban ideology generate unsustainable—even fatal—built environments, figuring two apocalypses as competing for space in suburban narratives: the concrete-grey and the green. In the grey, all hell breaks loose when the built environment can no longer deliver on suburban ideology's promises. But suburban ideology so drives American culture that hell must be displaced onto terrorists, weather, and parenting to make the future safe by keeping it recognizably suburban, literally concrete. The potential green apocalypse—what a return to nature would actually entail—critically engages the concrete-grey apocalypse, but at the cost of (suburban) life as we know its obsolescence.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.650

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0130.028
Scholarly communication0.0090.009
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.240
Teacher spread0.214 · 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 designQualitative
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

Citations5
Published2011
Admission routes1
Has abstractyes

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Same venueCanadian Review of American StudiesSame topicAmerican Environmental and Regional HistoryFrench-language works237,207