Media coverage of climate change: current trends, strengths, weaknesses
Bibliographic record
Abstract
This background paper provides a comprehensive survey of the role of the media in informing and communicating climate change. This paper looks at how media coverage has shaped discourse and action – in complex, dynamic and non-linear ways – at the interface of climate science and policy. Moreover, this work explores influences of media on practices, politics and public opinion and understanding related to climate change. Research on these interactions are delineated through work that has been undertaken in the United States, Canada, the United Kingdom, France, Germany, Japan, New Zealand, Australia, Honduras, Mozambique, Jamaica, Sri Lanka and Zambia, and explorations of newspaper coverage in forty English-language newspapers in seventeen countries, across five continents. Through these examinations of media coverage of climate change, links are made to related work on public perception and the relationship to international assistance.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".