Countering the Climate Change Counter Movement: Six lessons from Canada's climate delays
Bibliographic record
Abstract
The global transition away from fossil fuels is dangerously delayed. While climate delays are a complex issue, the fossil-fuel funded Climate Change Counter Movement represents a key culprit that is worthy of greater attention than it receives. As such, this article uses Canada as a case study to highlight the Movement's role in delaying climate action in the West, and to suggest six strategies to counteract their influence. We collate evidence demonstrating the Climate Change Counter Movement's influence over the Canadian state, its economy and its people, and directly linking elite members of the Movement to post-truth narratives that deny the reality of climate change, and delay climate policy. Concerningly, we also find evidence that these “climate delay discourses” can rapidly evolve to exploit new contexts and cultures, and are already being repeated by unassociated members of the general public. In order to spur action against the Climate Change Counter Movement, we combine insights from our case study with a narrative review of international research to suggest six strategies to counteract their influence, alongside associated directions for future research. These strategies would see climate policy advocates: reflect upon their own position; develop knowledge of the Climate Change Counter Movement's actions; use that knowledge to hold them legally accountable for those actions; reverse the effects they have already had on the general population; push “passively supported” policies to advance climate action even when public appetites are low; and challenge the economic and cultural roots of the Climate Change Counter Movement's power.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.048 | 0.025 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".