“No Action likely”: An Exploration of Institutional Bias Against Citizen Complaints about Wind Turbine Noise and Adverse Health Effects as Demonstrated by the Government in Ontario, Canada
Bibliographic record
Abstract
The Nation Rise wind power project was the last industrial-scale or grid-scale wind power project approved in Ontario, Canada despite controversy, opposition and legal action from the "host" community, and even an attempt by the environment minister himself to stop it.Problems surfaced early for the project, months before it was granted a formal commercial operation date, as residents complained of noise from the wind turbines.Documents including email correspondence referencing noise complaints made to the provincial government's environment ministry were obtained via Freedom of Information legislation.The Ontario Ministry of Environment, Conservation and Parks has a mandate to protect the environment and to enforce existing regulations.The documents appear to show that the environment ministry of the Government of Ontario had no intention of taking action on the citizen complaints.The only action evident was cursory responses to complaints, and simply logging events; no other action appears to have been taken by the staff in the environment ministry, which is the regulator for wind turbine power projects.Email correspondence between ministry staff and the wind power developer/operator demonstrates a casual, even cosy relationship, so much so that a senior environmental officer, representing the government as a regulator, actually asked the power plant operator what to do about the noise complaints.The correspondence may indicate institutional bias toward the operator, and against the public.Our findings: 1) Complaints about noise from wind turbines arose early on in this power generation project, before Commercial Operation date was determined as part of its contract.2) Ministry staff seem How to cite this paper:
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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 | 0.025 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.021 | 0.028 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".