Wind Turbines: An Exploration of Research Participants’ Living Experiences as a Consequence of Ontario’s Green Energy Act
Bibliographic record
Abstract
In 2009, the province of Ontario, Canada enacted the Green Energy Act.Those appealing an approval of a Wind Power Plant (WPP) were challenged by a high burden of proof-proof of causality.The requirement was that, before the project was constructed and operating, it must be shown that it "will cause" serious harm to human health, or "serious and irreversible harm" to plant or animal life, or the natural environment.Methods: This ethicsreviewed study used the Grounded Theory methodology.It conducted faceto-face interviews with those who had previously lived or were currently living within 10 km from a WPP.Audio files were transcribed to text, and the data were coded and analysed using NVivo Pro (v.12.6) software.Objectives: To explore and generate a substantive theory of the events that motivate research participants living within 10 km from a WPP to contemplate their housing decisions.Results: Data analysis revealed that the Green Energy Act #Until his death on February 12, 2023, Mr.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".