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Record W2893569697 · doi:10.17645/pag.v6i3.1432

Applying a Typology of Governance Modes to Climate Change Adaptation

2018· article· en· W2893569697 on OpenAlex
Danny Bednar, Daniel Henstra

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

VenuePolitics and Governance · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversity of WaterlooWestern University
Fundersnot available
KeywordsTypologyCorporate governanceAdaptation (eye)HierarchyScholarshipCLARITYPolitical scienceGovernment (linguistics)Public administrationMulti-level governanceCivil societyNetwork governancePublic relationsEconomic systemSociologyEconomicsManagementPolitics

Abstract

fetched live from OpenAlex

Climate change adaptation is a complex field of public policy that requires action by multiple levels of government, the private sector, and civil society. In recent years, increasing scholarly attention has been focused on the governance of adaptation, which has included exploring alternatives to state-centric models of decision-making and identifying appropriate roles and responsibilities of multiple actors to achieve desired outcomes. Scholars have called for greater clarity in distinguishing between different approaches to adaptation governance. Drawing on the rich scholarship about public governance, this article articulates and applies a typology of four modes of governance by which adaptation takes place (hierarchy, market, network, and community). Using examples of initiatives from across Canada, the article offers a framework for describing, comparing, and evaluating the governance of adaptation initiatives.

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)0.000
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 score0.938
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.044
GPT teacher head0.313
Teacher spread0.270 · 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