Trust in scientists, researchers, and environmental organizations associated with policy support for energy transition
Bibliographic record
Abstract
• The public supports policies that will directly benefit them. • The public trusts scientists, researchers, and non-profit organizations most. • Policymakers and decision makers could be more successful in gaining policy support by leveraging the public's trust in other actors. Energy transition, shifting away from fossil fuel use, is fundamental to addressing climate change. To explore public support for energy transition policies, we surveyed a representative sample of residents in Canada's largest province, Ontario, ( N = 1620), and conducted regression analyses to examine how support varies with trust in the actors communicating these policies. Ontarians prefer ‘carrot’ policies—those offering direct benefits to households—over ‘stick’ policies. The most supported policies include the development of renewable natural gas, interest-free energy efficiency loan programs, and funding for low-income energy efficiency programs, while the least supported policies are a carbon tax, continued oil sands development, and the electrification of heating. Ontarians have low to moderate levels of trust in governments at all levels, utilities, media, oil and gas companies, and to some extent in renewable energy companies. However they demonstrate consistently high trust in scientists, researchers, and non-profit organizations. Public support for policies in Ontario is influenced by trust in stakeholders and policymakers, with the relationship varying across different policies. We find Ontarians’ trust in scientists, researchers, and non-profit organizations is positively associated with supporting ‘emerging’ energy transition policies, such as the development of renewable natural gas and hydrogen. Our findings suggest that policymakers seeking to advance energy transition policies can strengthen both effectiveness and public acceptance by engaging with trusted actors, such as scientists and non-profits, and leveraging their credibility. Furthermore, adopting inclusive and participatory planning processes that reflect public values and address equity concerns is crucial to fostering long-term trust and policy stability amidst the challenges of the energy transition.
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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 | 0.010 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".