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Record W3142210198 · doi:10.1017/9781108920353.005

People and Place: Siting Wind and Solar Plants in Brazil and South Africa

2020· book-chapter· en· W3142210198 on OpenAlexaboutno aff
Kathryn Hochstetler

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyWind powerQuarter (Canadian coin)Solar powerLocal communityPower (physics)Environmental planningEnvironmental resource managementEconomyPolitical scienceEnvironmental protectionEcologyArchaeologyEconomics

Abstract

fetched live from OpenAlex

All infrastructure projects need to be placed in particular locations, and host communities typically have local populations, economies, and ecosystems that will be affected. The literature is divided, with energy and economic scholars tending to emphasize local benefits while geographers, anthropologists, and environmental scholars tend to highlight local costs. This chapter examines how local communities in Brazil and South Africa responded to new wind and solar power installations, asking not just about their preferences but also how (and if) they were able to mobilize resources and respond. Environmental impact assessment and land-use policies set a broad framework for these questions. New research conducted for the book finds that communities resisted wind power plants in about a quarter of the 77 Brazilian cities that hosted them, most in Brazil’s poor Northeastern region, especially in an early generation of poorly chosen coastal sites. There was little community protest against solar power in Brazil. South Africa saw little community protest against wind or solar power installations, though national organization BirdLife South Africa did strongly influence siting decisions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.962
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.196
Teacher spread0.181 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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