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Record W2012721369 · doi:10.1080/02722011.2014.914047

Newspaper Reporting on Climate Change, Green Energy and Carbon Reduction Strategies across Canada 1999–2009

2014· article· en· W2012721369 on OpenAlexaffabout
Conny Davidsen, Daniel Graham

Bibliographic record

VenueThe American Review of Canadian Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsClimate changeNewspaperKyoto ProtocolRenewable energyGreenhouse gasNatural resource economicsEcological modernizationModernization theoryClimate change mitigationPolitical scienceEconomicsEnvironmental resource managementBusinessEcologyEconomic growthSustainable developmentAdvertising

Abstract

fetched live from OpenAlex

Canada’s climate change strategy faces an uncertain future since the country’s withdrawal from the Kyoto Protocol in 2011, making domestic public debate and awareness critical in the search for effective mitigation policies. This article presents a spatio-temporal analysis of newspaper reporting across Canada on climate change and carbon reduction approaches, ranging from renewable energies (solar, wind, hydro power) to carbon management (e.g., carbon capture and storage [CCS]) and economic approaches (e.g., carbon trade, ecological fiscal reform). The findings of a news article keyword analysis show that the overall growth of the Canadian news coverage during this time period was significantly fragmented into isolated peaks of activity rather than continuous growth of the topic of climate change. Furthermore, the study finds a strong news emphasis on technology- and growth-oriented solutions as opposed to a comprehensive ecological modernization that would encourage a deeper structural discussion about Canada’s much-criticized carbon-intensive energy economy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.322
GPT teacher head0.448
Teacher spread0.126 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations11
Published2014
Admission routes2
Has abstractyes

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