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Advocacy Coalitions Along the Domestic‐Foreign Frontier: Globalization and Canadian Climate Change Policy

2000· article· en· W2146868461 on OpenAlexaboutno aff
Karen T. Litfin

Bibliographic record

VenuePolicy Studies Journal · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsFrontierGlobalizationContext (archaeology)Political scienceAutonomyForeign policyInternationalizationPoliticsPolitical economyPublic administrationEconomic systemSociologyEconomicsInternational tradeLawGeography

Abstract

fetched live from OpenAlex

With its emphasis on shared beliefs and the advocacy use of knowledge within policy subsystems, the advocacy coalition framework (ACF) is ideally suited to the study of environmental policy. Yet the ACF has generally been applied in a domestic context. This article argues that the twin phenomena of economic globalization and the internationalization of environmental affairs are blurring the distinction between some policy subsystems and the international arena. Thus, advocacy coalitions should be understood as operating increasingly along “the domestic‐foreign frontier.” In the case of Canada's efforts to develop a coherent climate change policy, the boundaries between political levels have been blurred as local and provincial actors come to understand themselves as players in a global game. This dynamic is exacerbated by Canada's unique constitutional division of authority, which delegates significant autonomy to the provinces on natural resource and energy issues.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.175
Threshold uncertainty score0.957

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0260.016
Scholarly communication0.0080.003
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.051
GPT teacher head0.388
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

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 designQualitative
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

Citations107
Published2000
Admission routes1
Has abstractyes

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