Have we Reached a “Tipping Point” in Climate Change Reporting? How Mainstream Newspapers Cover Heatwaves
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper investigates the evolution of media coverage on heatwaves from 2010 to 2022 focusing on six countries (UK, USA, India, Australia, Canada, and China) through analysis of 27,964 newspaper reports. By employing content analysis and named entity recognition, we examine the volume of heatwave-related reports, their connection to climate change, and the incorporation of environmental science within media narratives. We explain our findings with reference to the concept of a dynamic or mobile public sphere. We identify three types of diffusion in the reporting of climate change in public spheres, which we term temporal diffusion, geographical diffusion, and political diffusion. These concepts illustrate the spread of ideas across time, space, and ideology. These shifts are characterised by an escalating media focus on heatwaves over time and the increasing association between heatwaves and anthropogenic climate change, a diffusion from countries in the Global North to the Global South, and a broadening attention from predominantly left-wing media across a wider ideological spectrum. This study contributes to our understanding of how journalistic practice, accumulated media attention, and environmental science can lead to significant shifts in transnationally linked public spheres, encouraging broader societal recognition of and engagement with climate change issues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it