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Record W2112631315 · doi:10.1177/2158244012448487

Climate Change as a Wicked Problem

2012· article· en· W2112631315 on OpenAlex

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.

Bibliographic record

VenueSAGE Open · 2012
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsClimate changeWicked problemComplex adaptive systemDilemmaScale (ratio)Environmental resource managementSystems thinkingWater resourcesComputer scienceRisk analysis (engineering)Management scienceBusinessPolitical scienceEconomicsEpistemologyGeographyArtificial intelligenceEcology

Abstract

fetched live from OpenAlex

Understanding complexity suggests that some problems are more complex than others and defy conventional solutions. These wicked problems will not be solved by the same tools and processes that are complicit in creating them. Neither will they be resolved by approaches short on explicating the complex interconnections of the multiple causes, consequences, and cross-scale actors of the problem. Climate change is one such wicked problem confronting water management in Ghana with a dilemma. The physical consequences of climate change on Ghana’s water resources are progressively worsening. At the same time, existing institutional arrangements demonstrate weak capacities to tackle climate change–related complexities in water management. Therefore, it warrants a dynamic approach imbued with complex and adaptive systems thinking, which also capitalizes on instrumental gains from prior existing institutions. Adaptive Co-Management offers such an opportunity for Ghana to adapt its water management system to climate change.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.740

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.026
GPT teacher head0.240
Teacher spread0.213 · 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