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Record W2937730932 · doi:10.1177/0952076718814894

Have policy process scholars embraced causal mechanisms? A review of five popular frameworks

2019· review· en· W2937730932 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

VenuePublic Policy and Administration · 2019
Typereview
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsProcess (computing)Punctuated equilibriumMechanism (biology)Perspective (graphical)Process theoryNarrativePolicy analysisManagement scienceDevelopment theoryPositive economicsWork in processEpistemologySociologyPolitical scienceComputer scienceEconomicsPublic administration

Abstract

fetched live from OpenAlex

Over 30 years, several key frameworks and theories of the policy process have emerged which have guided a burgeoning empirical literature. A more recent development has been a growing interest in the application of a ‘causal mechanism’ perspective to policy studies. This article reviews selected theories of the policy process (Multiple Streams Approach, Advocacy Coalition Framework, Punctuated Equilibrium Theory, Narrative Framework Theory, and Institutional Analysis and Development Framework) and reports on an exploratory meta-analysis and synthesis to gauge the take-up of causal-mechanistic approaches. The findings suggest that there has been limited application of causal mechanisms and calls for more theoretical and empirical work on that aspect. Given the overlapping frameworks exploring different aspects of the policy process, further research informed by causal-mechanism approaches points to a new generation of inquiry across these and other policy process theoretical frameworks.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.076
GPT teacher head0.441
Teacher spread0.366 · 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