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Record W1966358931 · doi:10.1162/glep_a_00199

Wild Spaces or Polluted Places: Contentious Policies, Consensus Institutions, and Environmental Performance in Industrialized Democracies

2013· article· en· W1966358931 on OpenAlexaff
Joshua Ozymy, Denis Rey

Bibliographic record

VenueGlobal Environmental Politics · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsBiodiversityDemocracyEnvironmental governanceCorporate governanceFederalismClimate changeEconomicsEconomic systemPolitical sciencePoliticsEcologyBiology

Abstract

fetched live from OpenAlex

This article contributes to the literature on environmental governance in industrialized democracies by showing that effectively conserving biodiversity requires different institutional strategies than reducing air emissions. Institutional effectiveness diminishes as the politically contentiousness of the issue increases, moving from biodiversity to air pollution, and then climate change. Drawing on Lijphart's theory of consensus democracy and theories of functional and actorcentered federalism, we use the 2010 Environmental Performance Index and panel analysis on twenty-one OECD countries to show that consensus-based party systems improve performance. We find that centralization generates greater improvements with respect to air pollution than biodiversity, but that decentralized strategies can improve biodiversity when implemented alongside corporatist bargaining structures.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.005
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.211
Teacher spread0.180 · 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

Citations13
Published2013
Admission routes1
Has abstractyes

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