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Record W2101062324 · doi:10.1177/0010414013509575

The Micro Foundations of Policy Diffusion Toward Complex Global Governance

2013· article· en· W2101062324 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

VenueComparative Political Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsCorporate governanceDiffusionClimate changeProcess (computing)EconomicsGreenhouse gasEconomic systemEconomic geographyPublic economicsEcologyComputer scienceBiologyManagement

Abstract

fetched live from OpenAlex

Greenhouse gas emissions trading (ET) systems have become the centerpiece of climate change policy at multiple scales, unexpectedly largely outside of the UN climate governance process. The diffusion of ET is best described as a case of polycentric diffusion, where ET systems diffused to multiple loci of governance, but where they all serve similar goals under a broad policy framework guided loosely by the UN-based climate regime. Using network analysis combined with qualitative data, we explain how this polycentric pattern of policy development emerged, who carried and spread it and how, and how the idea has spread into a polycentric governance system. We contribute to the policy diffusion literature in a novel way to explain diffusion toward polycentric governance, show the limits of the existing literature to explain the diffusion of ET, and show the utility of network analysis in understanding the process and mechanism of polycentric diffusion.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.226
GPT teacher head0.480
Teacher spread0.254 · 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