Sustainable and Renewable Energy Development in Ontario: A look at the Current Policy Frameworks and Discourses Surrounding Sustainable Energy and Wind and Solar Power in Major Ontario Newspapers
Bibliographic record
Abstract
Over thirty years ago we celebrated the first Earth Day, which has since marked the preservation and restoration of the environment. Ironi-cally, since this re-dedication to environmentalism and renewed spirit in learning from the past we have worked to increase carbon emissions, oil consumption, natural gas, and coal extraction. Our “ecological footprint” has nearly tripled as a result of the growth of the global motor vehicle population, human carbon emissions and, of course, greenhouse gases and their partner global warming. The problem is not going to go away, and finding Canada’s place within the policy paradigm of sustainable development and environmental awareness will not be easy. Juxtaposed against a divided federalist state, environmental policy falls under the jurisdiction of the provincial government in this country, making it in-creasingly hard to adopt a policy framework that not only works, but works consistently across this country’s political, social and economic landscapes.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Analysis of Ontario renewable energy policy frameworks and their treatment in major newspapers; the object is energy policy and media discourse.
The article analyzes Ontario energy policy and newspaper discourse, not research practice.
Ontario sustainable energy policy analysis; energy policy, not research policy or systems.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.023 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".