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Record W3114403312 · doi:10.1177/2158244020983007

Debating Extractivism: Stakeholder Communications in British Columbia’s Liquefied Natural Gas Controversy

2020· article· en· W3114403312 on OpenAlexafffundabout
Sibo Chen

Bibliographic record

VenueSAGE Open · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPoliticsIdeologyCivil societyGovernment (linguistics)Political scienceLiquefied natural gasPolitical economyStakeholderNatural resourceCorporate governanceSociologyPublic administrationEconomicsLawNatural gas

Abstract

fetched live from OpenAlex

Shale gas extraction via hydraulic fracturing has been a controversial issue in many countries. In Canada, the provincial government of British Columbia (BC) has made relentless efforts on developing a liquefied natural gas (LNG) industry targeting potential Asian importers, which has been a heatedly debated public controversy since late 2011. Focusing on the two contending discourse coalitions formed by this policy initiative’s supporters and opponents, respectively, this article explores the intricate economic, political, and ideological struggles underlying Canadian extractivism. A qualitative discourse analysis of related stakeholder communications reveals that the pro-LNG coalition led by the BC Liberal government developed a “progressive extractivism” storyline to frame LNG exports as an unprecedented and ethical economic opportunity deserving the political support of environmentally minded British Columbians. By contrast, the anti-LNG coalition formed by progressive civil organizations, Indigenous groups, and concerned citizens engaged in fierce discursive resistance, notably via (a) adopting mainstream economic knowledge to highlight the fragile economic basis of BC LNG and (b) incorporating potent political issues such as democratic governance and reconciliation to expand public debates beyond the “jobs versus the environment” dichotomy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.247
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 teacher head, not a consensus.

Study designObservational
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
Published2020
Admission routes3
Has abstractyes

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