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Record W7055339229

Canadian Media Portrayal of Climate Change: An Investigation of Major Canadian Newspaper Outlets' Coverage of Federal Climate Change Action

2018· other· en· W7055339229 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2018
Typeother
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNewspaperClimate changeGovernment (linguistics)Scale (ratio)Action (physics)Audience measurementNews media
DOInot available

Abstract

fetched live from OpenAlex

This paper examines how four major Canadian newspaper outlets reported on climate change decisions by the federal government from 2007-2014. The paper analyzes 86 articles using criteria related to slant: language, tone and authorities; and depth of coverage by length of article. The analysis results organize the articles and then the outlets, on a scale from supportive to critical of action taken or not taken on climate change by the federal government. This scale was then juxtaposed with Canadian newspaper readership data to determine what type of coverage most Canadians are reading. \n \nIt was found that in most major Canadian cities the majority of citizens read Postmedia News, which generated very polar results in terms of this study. Upon further examination of journalists employed it was determined Postmedia is a more supportive outlet on federal climate change action. This may help explain the current public complacency on climate action in Canada.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.016
Science and technology studies0.0060.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.169
Teacher spread0.149 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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