Ontario’s Experience of Wind Energy Development as Seen through the Lens of Human Health and Environmental Justice
Bibliographic record
Abstract
The province of Ontario has shown great commitment towards the development of renewable energy and, specifically, wind power. Fuelled by the Green Energy Act (GEA) of 2009, the Province has emerged as Canada's leader in wind energy development (WED). Nonetheless, Ontario's WED trajectory is characterized by social conflicts, particularly around environmental health. Utilizing the Social Amplification of Risk Framework, this paper presents an eight-year longitudinal media content analysis conducted to understand the role Ontario's media may be playing in both reflecting and shaping public perceptions of wind turbine health risks. We find that before and after the GEA, instances of health risk amplification were far greater than attenuations in both quantity and quality. Discourses that amplified turbine health risks often simultaneously highlighted injustices in the WED process, especially after the GEA. Based on these findings, we suggest that Ontario's media may be amplifying perceptions of wind turbine health risks within the public domain. We conclude with policy recommendations around public engagement for more just WED.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".