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Record W4313441510 · doi:10.13033/isahp.y2022.014

ANALYZING EIA IN PARANÁ, BRAZIL AND CALIFORNIA, UNITED STATES WITH FUZZY-SET QUALITATIVE COMPARATIVE ANALYSIS AND THE ANALYTICAL HIERARCHY PROCESS

2022· article· en· W4313441510 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

VenueISAHP proceedings · 2022
Typearticle
Languageen
FieldDecision Sciences
TopicMulti-Criteria Decision Making
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsStakeholderQualitative comparative analysisNormativeStakeholder analysisSustainable developmentManagement scienceProcess managementOutcome (game theory)Environmental resource managementPolitical scienceComputer scienceBusinessEngineeringPublic relationsEconomics

Abstract

fetched live from OpenAlex

Since its introduction in the US, environmental impact assessment (EIA) has become one of the most widespread environmental policy instruments, which has evolved from solely conservation aims to serve as a tool for sustainable development.Despite its history and dissemination, EIA is routinely criticized for being ineffective at impacting decision-making or promoting more sustainable development.This study performed a comparative case study using the effectiveness dimensions from the EIA evaluative literature and two methodologies.Two states in federalist systems were chosen, Paran, Brazil and California, United States.This comparative case study formats the cases into contextual conditions using the fuzzy-set Qualitative Comparative Analysis (fsQCA) methodology in order to identify the necessary and sufficient conditions that foster effective outcomes.These effectiveness outcomes and criteria are then ranked by EIA stakeholders via the analytical hierarchy process (AHP) in order to identify stakeholder priorities and to improve stakeholder management.The results show that in Paran stakeholders identified normative effectiveness as the most important dimension for an ideal effective EIA outcome, and stakeholders in California identified this dimension as the second-most important following substantive effectiveness.For normative effectiveness outcome early project definition and public participation were found to be necessary conditions and stakeholder coordination was found to be a sufficient condition.Following normative effectiveness, Paran stakeholders identified procedural effectiveness as the second most important.While transactive effectiveness was ranked lowest overall in both case studies, improving procedural effectiveness has been shown to be connected to the transactive effectiveness.Finally, transformative effectiveness ranked third and fourth in California and Paran respectively, which also had the lowest set membership in fsQCA.This study advances EIA evaluatory literature by assessing various effectiveness dimensions through two complementary methodologies.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.912

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.011
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.125
GPT teacher head0.462
Teacher spread0.337 · 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