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Record W2083955065 · doi:10.3152/146155108x279939

Contentious politics in environmental assessment: blocked projects and winning coalitions

2008· article· en· W2083955065 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImpact Assessment and Project Appraisal · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSustainabilityPoliticsPublic participationPolitical sciencePublic administrationScale (ratio)Environmental impact assessmentPublic domainEnvironmental planningBusinessPublic relationsLawGeography

Abstract

fetched live from OpenAlex

Environmental assessment (EA) is now institutionalized in over 100 countries but is widely criticized by practitioners and analysts for failing to convince decision-makers. Environmental sustainability is still not placed high on the list of criteria influencing project and programme approvals. This paper suggests that the failure of EA reflects the politically contested domain of EA. A framework for the analysis of public participation in EA based on the study of contentious politics is introduced. Public participation is a crucially important condition for influencing decision makers to pursue sustainability objectives, but the effectiveness of public participation is conditional upon characteristics of the coalitions created by diverse stakeholders. The importance of coalitions between local stakeholders and intellectuals is highlighted and exemplified through four cases in the Philippines, Brazil, South Africa and Taiwan where public participation in EA processes is associated with the blockage of large-scale development projects.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.367
Teacher spread0.335 · 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