Energy and Energy Literacy in Canada: A Survey of Business and Policy Leadership
Bibliographic record
Abstract
Lots of people have opinions about Canadian energy, how we use and export it, its costs and its impacts on the environment. In the end, however, it is leaders in business and policy circles whose opinions can have a greater impact on influencing how the rest of us think about energy, and ultimately, how our national energy picture eventually unfolds. Remarkably, however, a survey of leaders in business and policy-making across the country finds that their knowledge about Canadian energy systems is not that much deeper or different than the Canadian public at large. Their opinions about how we should use, conserve and export energy are also strikingly similar. Anyone presuming that leaders in business and policy have a firm understanding of how Canadians get their energy might be startled to discover that, in Ontario, Alberta, the Atlantic region and Saskatchewan, a substantial fraction of these “elite” survey respondents incorrectly identify the primary resource used for energy in their province. Nor are business and policy leaders the ardent free traders some of us might expect when it comes to energy exports and imports. While an overwhelming majority (89 per cent) of survey respondents considered it important or at least somewhat important to decrease Canada’s reliance on the U.S. market for our exports, 56 per cent of those surveyed also advocated for more Canadian energy independence, even if it meant reduced revenue for the Canadian economy. Not only that, but they largely believed that eliminating energy imports and relying exclusively on Canadian sources would somehow result in an overall drop in energy costs. Furthermore, a strong majority of policy-makers and business leaders had a general agreement that it was worth bearing higher energy costs in the future if it resulted in better environmental quality. Additionally, when it came to evaluating who they could trust for reliable information about energy, business and policy-making elites proved just about as skeptical as the general public when it came to companies, industry groups and government officials, ranking all three fairly weakly on trustworthiness. They saw academics and economic experts as slightly more trustable sources for information, though even those sources had limits. And while environmental and community groups and activists were given generally middling scores for trustworthiness, business leaders, interestingly enough, actually ranked these activist groups as just a bit more reliable than did policy-makers. Finally, a clear preference in both groups was revealed for more planning and systematically adapting to changing energy markets and environmental conditions through the development of some form of public policy energy strategies.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".