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Record W4317797504 · doi:10.32920/21944084

Debating Resource-Driven Development: A Comparative Analysis of Media Coverage on the Pacific Northwest LNG Project in British Columbia

2023· preprint· en· W4317797504 on OpenAlexafffundabout
Sibo Chen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLiquefied natural gasNewspaperGovernment (linguistics)Media coverageResource (disambiguation)Political scienceMass mediaBusinessAdvertisingEconomyEngineeringEconomicsMedia studiesNatural gasSociology

Abstract

fetched live from OpenAlex

In Canada, the provincial government of British Columbia has been keen on building an export-oriented liquefied natural gas (LNG) industry since 2011. This paper examines media coverage of the Pacific NorthWest LNG project (PNW), which was considered as the flagship proposal leading the BC LNG development, until its abrupt cancellation in July 2017. The paper explores the differences between public, commercial, and independent media in energy reporting by tracing how six Canadian media outlets covered the rise and fall of PNW over a 36 month period. The comparative analysis reveals that when addressing the project's cancellation, fossil fuel advocates repeatedly deployed the "jobs killed by environmentalists" argument via opinion pieces appearing in commercial newspapers. This diagnosis, however, downplayed the far-reaching impacts of falling Asian LNG market conditions prior to the cancellation. By comparison, independent media played an important role in assisting LNG opponents to communicate PNW's fragile economic basis to a wide audience. Overall, these findings shed light upon the significance of independent media in supporting diverse news accounts of energy controversies.

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)0.002
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.015
Science and technology studies0.0050.002
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.278
Teacher spread0.227 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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