Comparing Climate Change Coverage in Canadian English and French-Language Print Media: Environmental Values, Media Cultures, and the Narration of Global Warming
Bibliographic record
Abstract
This article compares how climate change is presented in English- and French-language print media in Canada. In recent years, climate change has become an increasingly divisive issue, with the media playing a central role in the promotion of competing claims and narratives in the public sphere. Using concepts from environmental sociology and the sociology of journalism, we examine content from six English- and two French-language newspapers from 2007-2008 (N=2,245), and find significant evidence of both convergence and divergence across the language divide. Among the most significant findings are differences in how complexity is handled: English outlets present diverse coverage that is highly compartmentalized, while the French newspapers present a narrower range of coverage but with thematically richer articles that better link climate change issues to the realms of culture, politics, and economy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".