Public Attitudes Toward Climate Science and Climate Policy in Federal Systems: Canada and the U.S. Compared
Bibliographic record
Abstract
Despite a great deal of scientific evidence in support of global warming, the public remains deeply divided on whether global warming is occurring and on what policies should be enacted in response. In the context of wide variation in climate policy at both national and sub-federal levels, this paper utilizes an original data set to examine public attitudes and perceptions toward climate science and climate change policy in two federal systems. Using national and provincial/state level data from telephone surveys administered to random probability samples in Canada and the U.S. during 2010 and 2011, the paper provides insight into where the public stands on the climate change issue in two of the most carbon-intensive federal systems in the world. The paper includes the first directly comparable public opinion data on how Canadians and Americans form their opinions regarding climate matters, and provides insight into the preferences of these two populations regarding climate policies at both the national and sub- national levels. Building on previous studies of public opinion in the U.S., which finds strong associations between political predispositions, on the one hand, and views on climate change, on the other, the paper further examines the determinants of individual beliefs in cross-national perspective. Key findings are examined in the context of growing policy experiments at the sub-federal level in both countries and limited national level progress in the adoption of climate change legislation.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".