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Record W4283792056 · doi:10.1177/23996544221111657

The urban politicization of fossil fuel infrastructure: Mediatization and resistance in energy landscapes

2022· article· en· W4283792056 on OpenAlexafffundabout
Sophie L. Van Neste, Annabelle Couture-Guillet

Bibliographic record

VenueEnvironment and Planning C Politics and Space · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsMcGill University
FundersFonds de Recherche du Québec-Société et CultureInstitut national de la recherche scientifique
KeywordsConceptualizationCorporate governancePoliticsResistance (ecology)Urban politicsIndigenousPolitical scienceSociologyWork (physics)Political economyEnvironmental planningGeographyLawBusinessEngineeringEcology

Abstract

fetched live from OpenAlex

From 2013 to 2016, two pipeline projects were vigorously contested in the Tiohtià:ke: Montreal area in Quebec, Canada. These disputes are analyzed as instances of the urban politicization of fossil fuel infrastructure. This politicization involves power struggles for authority in energy landscapes, particularly in relation to the material entanglement of energy in the city-region, that is, which parts of the infrastructure and landscapes come to matter. Drawing on work from political ecologists and scholars pressing for a rematerializing of urban studies, we supplement their insights with a conceptualization of struggles for urban authority in the governance of energy, in two parallel processes: one of performing centralized urban authority (notably with the media) and a second messier politics of multiplicities operating in spaces of urban governance and resistance. Struggles for urban authority are co-constructed with the socio-material realities of infrastructure and involve actors who are engaged in everyday practices of regulating, maintaining and protecting landscapes. Yet, in the mediatization of urban energy landscapes, certain voices, notably of Indigenous communities, remain on the margins, resulting in few challenges to settler colonialism and climate-changing extractivism.

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)0.006
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 score0.215
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0100.023
Scholarly communication0.0130.005
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.004
GPT teacher head0.202
Teacher spread0.198 · 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

Citations8
Published2022
Admission routes3
Has abstractyes

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