Wind turbines: Vacated/abandoned homes study – Exploring research participants’ descriptions of observed effects on their pets, animals, and well water
Bibliographic record
Abstract
Abstract Background: Neighbors living within 10 km of industrial wind turbines have reported occurrences of adverse health effects and contemplated vacating their homes. Some participants described concerns for wildlife and effects on their pets, animals, and well water. While sources such as the scientific literature, social media, and Internet websites have reported these effects, research is limited. Methods: This ethics-reviewed study used the qualitative grounded theory methodology and interviewed 67 consenting participants, 18 years or older who had previously lived, or were currently living within 10 km of wind turbines. Audio files were transcribed to text, and the data were coded and analyzed using NVivo Pro (version 12.6) software. Objectives: The objectives of this study were to explore participants’ descriptions of effects related to their pets, animals, and well water and to generate a theory. Results: Data analysis revealed primary themes of environmental interference and altered living conditions and associated sub-themes of effects on animals and well water. Discussion: Internationally and in Ontario neighbors have reported effects on their pets and domestic animals, concerns for wildlife, and a loss of potable well water. It is recommended that members of the public, government authorities, policy-makers, researchers, health practitioners and social scientists with an interest in health policy acknowledge the potential for these effects and seek resolution for those negatively affected.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".