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Record W4368375829 · doi:10.1002/eet.2057

Barriers and enablers of environmental policy coherence: A systematic review

2023· review· en· W4368375829 on OpenAlexaff
Alain Fopa Tchinda, David Talbot

Bibliographic record

VenueEnvironmental Policy and Governance · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsEnvironmental policyCoherence (philosophical gambling strategy)Systematic reviewField (mathematics)Process (computing)SociologyPolitical scienceManagement scienceEngineering ethicsProcess managementKnowledge managementEnvironmental resource managementBusinessEngineeringComputer scienceEconomicsMEDLINE

Abstract

fetched live from OpenAlex

Abstract The literature on policy coherence (PC) examines contradictions and synergies between policies. This systematic review explores factors that facilitate or disrupt PC in the environmental field. Based on 70 empirical studies, this research describes the evolution of the PC literature, identifying eight critical PC factors. Furthermore, this study identifies six avenues for future research on PC, such as methodological innovations and including stakeholders in the policy development process. In addition to drawing on contradictions and synergies for PC analysis, this study suggests an integrative framework of barriers and enablers. These findings have implications for policymakers and program managers in the environmental field.

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)0.021
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.076
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0150.016
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0020.002
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 head0.019
GPT teacher head0.282
Teacher spread0.262 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations19
Published2023
Admission routes1
Has abstractyes

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