Fire and Climate: Connecting the Dots in British Columbia News Media
Bibliographic record
Abstract
Background: Extreme weather events are intensifying with climate change, offering opportunities to raise the public urgency of this issue. The media’s role in communicating this connection is crucial. Analysis: This article analyzes media coverage of wildfires over a nine-year period in British Columbia focusing on how they are linked to climate change, in particular, during the 2017 and 2018 record-breaking fire seasons. Conclusion and implications: In media coverage in British Columbia, there is a marked absence of a link between climate change and wildfires and a tendency for connections to be tokenistic, decontextualized, and normalizing. More provocative narratives developed by various public figures that locate wildfires within broader narratives of climate crisis offer more compelling accounts. Contexte : À cause du changement climatique, les événements climatiques extrêmes sont en train de devenir plus intenses. Dans les circonstances, il devient pertinent de soulever l’urgence publique de cet enjeu, et les médias pourraient jouer un rôle crucial pour le communiquer. Analyse : Cet article analyse la couverture médiatique de feux de forêt sur une période de neuf ans en Colombie-Britannique, particulièrement durant les saisons des feux de 2017 et 2018 qui ont battu tous les records. L’article met l’accent sur comment ces incendies sont reliés au changement climatique. Conclusions et implications : Dans la couverture médiatique en Colombie-Britannique, on néglige de montrer les liens qui existent entre le changement climatique et les feux de forêt. Toute connexion établie tend à être superficielle, décontextualisée et normalisée. En revanche, diverses personnalités publiques ont incorporé les feux de forêt dans des narrations englobant l’idée de crise climatique, offrant ainsi une perspective plus intéressante, voire provocatrice.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".