Beach day or deadly heatwave? Content analysis of media images from the 2021 Heat Dome in Canada
Bibliographic record
Abstract
Abstract During extreme heat events (EHEs) the public often learns about health protective actions through the media. Visual news coverage can act as a powerful tool to help convey complex health protective actions to the public. Despite the importance of images in helping the public understand the risk, there has been no systematic analysis to assess what images have been used by media outlets in Canada during EHEs. This paper helps to fill that gap by analyzing how the Canadian media visually communicated the risks of extreme heat to the public during the unprecedented 2021 Heat Dome. A review of thousands of online news media articles published about the 2021 Heat Dome in Canada was conducted on five subscription news databases. Overall, 845 images were coded to identify denotative, connotative, and ideological content. Only 16% of these published images implied that heat was dangerous, of which only 40% depicted people, and 46% implied human suffering. Our findings demonstrate that the majority of images used in Canadian news coverage on the 2021 Heat Dome are incompatible with, and frequently contradict, evidence-based heat protective actions. Governments, public health agencies, and other stakeholders engaged in distributing heat preparedness messaging (e.g., journalists) should prioritize improving the images of extreme heat in news coverage to align with evidence-based public health messages. With rising global temperatures due to climate change and the associated increases in the frequency and intensity of extreme heat events, prioritizing these actions is critically important to offset the threat posed to public health.
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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 | 0.001 |
| 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) | 0.006 | 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".