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Record W2115881843 · doi:10.1111/ropr.12001

Policy Capacity for Climate Change in<scp>C</scp>anada's Transportation Sector

2013· article· en· W2115881843 on OpenAlexaff
Joshua Newman, Anthony Perl, Adam Wellstead, Kathleen McNutt

Bibliographic record

VenueReview of Policy Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsUniversity of ReginaSimon Fraser University
Fundersnot available
KeywordsPolicy analysisClimate changeGovernment (linguistics)MacroBusinessPolicy studiesRegional sciencePublic policyPublic administrationEconomicsPolitical scienceComputer scienceEconomic growthSociology

Abstract

fetched live from OpenAlex

Abstract When pursuing change, legacies of policy goals and instruments from an established paradigm often present constraints on fully embracing a newer paradigm, resulting in the layering of new policy goals and instruments on top of the existing base. In this article, we investigate the effect of layered paradigms on policy capacity at three different levels of policy making in theCanadian transportation sector. Using analysis of government publications and budget data, virtual policy network analysis, quantitative analysis of data from a survey ofCanadian policy analysts, and direct interviews with policy managers in two provinces, we demonstrate how this layering of legacy goals (and consequent policyincapacity) is occurring at the macro, meso, and micro levels of policy making. We conclude that the layering of a new policy paradigm for climate change on top of the established paradigm for transportation development constrains policy capacity in this subsystem.

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)0.007
metaresearch head score (Gemma)0.014
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: Empirical
Teacher disagreement score0.981
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.003
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.211
GPT teacher head0.488
Teacher spread0.277 · 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

Citations16
Published2013
Admission routes1
Has abstractyes

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