Comparing Newspaper Coverage of Climate Change During Election Campaigns in the United States, Canada and Australia
Bibliographic record
Abstract
This study compares newspaper coverage of climate change and global warming during the national elections in Australia, Canada and the U.S. during 2007 and 2008. Using a census of newspaper coverage and in-depth interviews with reporters, editors and columnists in the three countries, the study confirmed the findings of earlier studies that the political agenda shapes the news agenda when it comes to climate change coverage. However, the study did find that coverage of general climate change stories continued during the election campaign periods in the three countries. Reporters who cover either politics or environmental issues or both found it difficult to make the connection in their stories between climate change concerns and the political debate, even in the case of the 2007 Australian and 2008 Canadian elections where climate change policy was a major issue. These problems highlight the need for newspapers to seriously reconsider how they approach coverage of climate change in general and in the political context by making more connections to related stories outside of the geographic area that they serve.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".