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Record W4393343316 · doi:10.4103/ed.ed_2_23

Wind turbines: Vacated/abandoned homes study – Exploring research participants’ descriptions of observed effects on their pets, animals, and well water

2024· article· en· W4393343316 on OpenAlexaffabout
Carmen Marie Krogh, Robert Y. McMurtry, W. Ben Johnson, Jerry L. Punch, Anne Dumbrille, Mariana Alves‐Pereira, Debra Hughes, Linda Rogers, Robert W. Rand, Lorrie Gillis

Bibliographic record

VenueEnvironmental Disease · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsPrince County HospitalWestern University
Fundersnot available
KeywordsWildlifeGrounded theoryGovernment (linguistics)Qualitative researchWind powerPsychologySocial mediaEnvironmental healthApplied psychologyPublic relationsBusinessGeographySocioeconomicsSociologyMedicineEngineeringPolitical scienceEcologySocial science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.132
GPT teacher head0.290
Teacher spread0.158 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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