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Record W2606030346 · doi:10.1215/00382876-3829511

What Can Art Do about Pipeline Politics?

2017· article· en· W2606030346 on OpenAlexaboutno aff
Brian Holmes

Bibliographic record

VenueSouth Atlantic Quarterly · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsGrassrootsPoliticsTipping point (physics)Oil refineryContentious politicsPolitical scienceEnvironmental justicePolitical economyBoomSocial movementSociologyEngineeringLaw

Abstract

fetched live from OpenAlex

This text explores the consequences of the massive flow of Canadian heavy crude oil from the Alberta Tar Sands to the Chicago metropolitan area. The boom in North American oil extraction has literally strained petroleum infrastructure to its bursting point. How do urban populations react to the intensifying pressure of “pipeline politics” on their daily lives? In the Chicago case, at least some of them have responded with grassroots mobilization, cultural engagement, and the timid beginnings of institutional transformation. The interplay between community activists threatened by a refinery by-product (petroleum coke, or petcoke) and experimental artists seeking to engage both immediate environmental justice issues and long-term problems of climate change offers insights into the complex social formations that may someday shift the present suicidal course of advanced industrial economies, if voluntary blindness, managed oblivion, and pervasive institutional paralysis can be overcome through the exercise of what I call a “politics of perception.”

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.039
Scholarly communication0.0180.018
Open science0.0010.004
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0210.004

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 head0.008
GPT teacher head0.211
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
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

Citations3
Published2017
Admission routes1
Has abstractyes

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Same venueSouth Atlantic QuarterlySame topicAmerican Environmental and Regional HistoryFrench-language works237,207