Creating and testing a survey to assess the impact of renewable energy technologies on quality of life
Bibliographic record
Abstract
With the increasing concerns regarding fossil fuels and nuclear energy, greater attention is being placed on alternate renewable energy technologies (RETs) such as wind, solar, and bioenergy. However, implementation of modern RETs has become controversial, as adverse health effects are a major concern. Although local case studies have suggested a relationship between wind turbines and health, there is a gap in the scientific knowledge. Epidemiological studies with adequate data collection tools and analyses are needed, particularly in the Canadian context. We reviewed surveys used in relevant environmental health literature, created a data collection tool for use in populations exposed to wind turbines, and piloted the survey content and distribution method. Our pilot response rate was 25.5% (45/200). The mean age of survey respondents was 57.6 years (SD: 12.76) with 57% of the respondents being female; respondents were not significantly different than the target population with respect to age or sex. The survey and methods presented here can be used in future studies to assess the health impacts of renewable energy technologies.
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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 | 0.050 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".