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Record W3005549329 · doi:10.1177/0952076720904434

Strategic policy narratives: A narrative policy study of the Columbia River Crossing

2020· article· en· W3005549329 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePublic Policy and Administration · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeScope (computer science)Public policyPublic administrationProcess (computing)SociologyPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

This study examines how coalitions in local policy contexts implore policy narratives to expand or contain the scope of policy issues. The Narrative Policy Framework (NPF), a maturing theory of the policy process, is utilized in this study to conduct content analysis on 370 public documents from competing coalitions in relation to the Columbia River Crossing project; a “wicked” policy issue in the Portland, OR/Vancouver, WA region of the Pacific Northwest. From this case selection, it is hypothesized that competing coalitions will use narrative strategies of containment and expansion to achieve their desired policy outcomes. It is also theorized that shocks to a policy subsystem may result in a shift to coalitional narrative strategies. This research will shed light on how coalitions strategically implore policy narratives in cohesive and less cohesive ways to influence policy outcomes.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
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 head0.080
GPT teacher head0.370
Teacher spread0.290 · 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