Post‐tropical cyclone Fiona and Atlantic Canada: Media framing of hazard risk in the Anthropocene
Bibliographic record
Abstract
Post-tropical cyclone Fiona made landfall in Nova Scotia, Canada, in September 2022 with the force of a Category 2 hurricane. Using 'risk society' as an analytical framework, and Thomas A. Birkland's 'focusing event' concept, this paper seeks to understand how publics construct risk in the context of climate change and how institutions engage with those narratives. A qualitative content analysis of 439 newspaper articles from across Canada reveals that most media provide a superficial description of hazard impacts. When media are critical, they connect Fiona to climate change, other extreme events, social vulnerability, and systemic inequality. In response to Fiona and industry trends, insurance representatives indicate a withdraw from covering low-probability, high-consequence events owing to ambiguity in risk analysis and financial interests, complicating hazard relief. Political actors' rhetoric is strong-delivering relief in unprecedented ways and offering new adaptive policy. However, a history of unfulfilled political promises to act on climate change elicits scepticism from media sources.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".