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Record W2581561765 · doi:10.36939/cjur/vol25no2/art47

Exploring the Socioeconomic Composition of Wind Farm Communities in Ontario: Implications for Wind Farm Planning and Policy

2016· article· en· W2581561765 on OpenAlexaffvenueabout
Matthew Quick, Jane Law, Tanya Christidis, Claire Paller

Bibliographic record

VenueCanadian journal of urban research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDisadvantagedSocioeconomic statusGeographyOffshore wind powerIncentiveAgricultural economicsWind powerBusinessEconomic growthEngineeringEconomicsSociologyDemographyPopulation

Abstract

fetched live from OpenAlex

This research explores the socioeconomic composition of sixteen wind farm communities in Ontario, Canada, for wind farms commissioned between 2006 and 2012. Past research has shown that wind farms are disproportionately developed in socioeconomically disadvantaged areas and that socioeconomic factors influence wind farm support, an important factor in wind farm planning. This research finds that wind farm communities do not exhibit characteristics of disadvantage compared to host counties. Investigating the association between when wind farms were commissioned and community-scale characteristics, this research observes that communities with wind farms operational before 2009 had significantly lower median income compared to communities with wind farms operational after 2009. This provides one perspective on how community-scale characteristics may shape wind farm planning, specifically the influence of local opposition and financial incentives on the location of wind farm developments.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.221
GPT teacher head0.383
Teacher spread0.162 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes3
Has abstractyes

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