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Record W1729052875 · doi:10.1111/ropr.12004

Climate Change Adaptation and Policy Capacity in the Canadian Finance Sector: A Meso Analysis

2013· article· en· W1729052875 on OpenAlex
Russell Alan Williams, Kathleen McNutt

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueReview of Policy Research · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of ReginaMemorial University of Newfoundland
Fundersnot available
KeywordsOperationalizationClimate changeCorporate governanceAdaptation (eye)Climate change adaptationPolicy analysisPolitical economy of climate changeAdaptive capacityClimate policyEconomicsPublic economicsEnvironmental resource managementBusinessRegional sciencePolitical scienceFinancePublic administrationSociology

Abstract

fetched live from OpenAlex

Abstract This article examines policy capacity in relation to climate change adaptation in the C anadian finance sector. Through a meso‐level analysis focused on the level of integration of the finance policy network and a survey of policy professionals in the area regarding climate change issues, the article illustrates both challenges to operationalizing the concept of “policy capacity” and limitations to effective policy capacity on climate change in this policy domain. Though a central concern for governments, improvements in policy capacity require more attention to network integration and governance arrangements if governments are to effectively respond to the unique challenges posed by climate change adaptation.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.511
GPT teacher head0.395
Teacher spread0.115 · 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