Creating and testing a survey to assess the impact of renewable energy technologies on quality of life
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it