Anthropogenic climate change coverage in two Canadian newspapers : the Toronto Star and the Globe and Mail, from 1988-2007
Bibliographic record
Abstract
Media portrayal of current events can influence public perception and the actions that policy and decision makers take with regard to these events. This study applied a content analysis to explore variations in the way Canadian news media depicted anthropogenic climate change by employing an approach previously used by Liu, Vedlitz and Alston (2008). This research applied their existing methodology to both the regional and national levels of media in a Canadian setting. Climate change articles from two newspapers published between 1988 and 2007, the Toronto Star, a regional newspaper, and the Globe and Mail, a national newspaper, were obtained. They were examined for aspects of climate change, including salience, image, scope, country representation, participants, and the origins of scientific information that was presented in the articles. Differences in the way climate change is portrayed between the newspapers at regional and national levels are also examined. Overall, climate change is portrayed similarly in the two newspapers as a large-scale (national and global) problem, despite the differences in audience scope. The Toronto Star exhibits a more national perspective with respect to climate change although it is a regional newspaper. Attention paid by the media to climate change increases from 1988-2007. Climate change is predominantly depicted in both newspapers as a destructive issue. There are linkages to other public issues, including those in international co-operation, science research and development, and energy and transportation. The analysis reveals that a number of non-government and government actors are concerned with climate change and a wider array of interest groups is becoming involved. Finally, the majority of the solution strategies presented in the articles focus on mitigation techniques, as opposed to adaptation strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".