Media and Climate Change Observatory Monthly Summary: Life as We Know It - Issue 29, May 2019
Bibliographic record
Abstract
May media attention to climate change and global warming was up 27% throughout the world from the previous month of April 2019. While coverage in the Middle East dropped 25% from the previous month, coverage in all other regions increased from April 2019 into May 2019: among them, African coverage doubled, Asian media attention to climate change was up nearly 12%, European coverage increased nearly 22%, Central/South American coverage was up 23%, North America coverage increased almost 8% and coverage on Oceania rose over 86% compared to the previous month. Across international wire services – Associated Press, Agence France Presse, The Canadian Press and United Press International - media attention to climate change went up nearly 20%, while across international radio programming including American Public Media, National Public Radio, British Broadcasting Services, Southwest Radio Africa, Radio Balad and Radio France Internationale – media coverage increased nearly 30%. Figure 1 shows trends in newspaper media coverage at the global scale – organized into seven geographical regions around the world – from January 2004 through May 2019.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".