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Record W2590583097 · doi:10.1111/ropr.12236

Climate Adaptation in Canada: Governing a Complex Policy Regime

2017· article· en· W2590583097 on OpenAlexafffundabout
Daniel Henstra

Bibliographic record

VenueReview of Policy Research · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAdaptation (eye)Corporate governancePerspective (graphical)Collective actionGovernment (linguistics)Public policyPublic administrationPolitical scienceAction (physics)Climate change adaptationClimate changeEconomicsPoliticsManagementLawEcology

Abstract

fetched live from OpenAlex

Abstract Climate adaptation is a complex policy area, in which knowledge, authority, and resources are fragmented among numerous public agencies, multiple levels of government, and a wide range of nongovernmental actors. Mobilizing and coordinating disparate public and private efforts is a key challenge in this policy domain, and this has focused research attention on the governance of adaptation, including the dynamics of interaction among interests and the institutions that facilitate collective action. This paper contributes to the study of adaptation governance by adopting the policy regimes perspective, an analytical framework designed to make sense of the loose governing arrangements surrounding complex, fragmented problems. The perspective's constructs are applied to a longitudinal case study of adaptation governance in Canada, which identifies, analyzes, and evaluates the policy ideas, institutions, and interests that comprise Canada's adaptation policy regime.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0110.012
Scholarly communication0.0090.002
Open science0.0020.003
Research integrity0.0020.002
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 head0.184
GPT teacher head0.440
Teacher spread0.257 · 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 designNot applicable
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

Citations43
Published2017
Admission routes3
Has abstractyes

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