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Record W4310154772 · doi:10.3390/socsci11120552

Analysis of the Relevance of the Advocacy Coalition Framework to Analyze Public Policies in Non-Pluralist Countries

2022· article· en· W4310154772 on OpenAlexaff
Viengsamay Sengchaleun, Hina Hakim, Sengchanh Kounnavong, Daniel Reinharz

Bibliographic record

VenueSocial Sciences · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRelevance (law)ChinaPolitical sciencePublic policyPublic relations

Abstract

fetched live from OpenAlex

The Advocacy Coalition Framework (ACF) is a theoretical approach developed for the study of the emergence of public policies in pluralist countries. Little is known about the relevance of the framework for the study of policies in non-pluralist countries (NPCs). A review of the literature was conducted on the use of ACF in studies performed in NPCs. Nineteen documents were identified. They were based on studies conducted in China, Laos, and Vietnam. The results show that the ACF is a powerful theoretical approach for highlighting the dynamics of interactions between coalitions that exist in NPCs, as in pluralist countries, and for highlighting their specificity. ACF is a relevant tool for the study of the determinants of the emergence of public policies in NPCs.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.010
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.032
GPT teacher head0.368
Teacher spread0.335 · 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 teacher head, not a consensus.

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

Citations5
Published2022
Admission routes1
Has abstractyes

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