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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 OpenAlexaffabout
Danny Bednar, Daniel Henstra

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.

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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0060.006
Science and technology studies0.0050.024
Scholarly communication0.0080.010
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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

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 designTheoretical or conceptual
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
Published2018
Admission routes2
Has abstractyes

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