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Record W3141526719 · doi:10.1111/1758-5899.12932

Climate Ambition and Sustainable Development for a New Decade: A Catalytic Framework

2021· article· en· W3141526719 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

VenueGlobal Policy · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsImpactYork University
Fundersnot available
KeywordsOrchestrationAction (physics)Climate governanceAccountabilityCorporate governanceSustainable developmentBusinessPolitical scienceState (computer science)Process managementEnvironmental resource managementEnvironmental planningComputer scienceEconomicsEnvironmental science

Abstract

fetched live from OpenAlex

Abstract This paper examines the Global Climate Action Agenda (GCAA) and discusses options to improve sub‐ and non‐state involvement in post‐2020 climate governance. A framework that stimulates sub‐ and non‐state action is a necessary complement to national governmental action, as the latter falls short of achieving low‐carbon and climate‐resilient development as envisaged in the Paris Agreement. Applying design principles for an ideal‐type orchestration framework, we review literature and gather expert judgements to assess whether the GCAA has been collaborative, comprehensive, evaluative and catalytic. Results show that there has been greater coordination among orchestrators, for instance in the organization of events. However, mobilization efforts remain event‐driven and too little effort is invested in understanding the progress of sub‐ and non‐state action. Data collection has improved, although more sophisticated indicators are needed to evaluate climate and sustainable development impacts. Finally, the GCAA has recorded more action, but relatively little by actors in developing countries. As the world seeks to recover from the COVID‐19 crisis and enters a new decade of climate action, the GCAA could make a vital contribution in challenging times by helping governments keep and enhance climate commitments; strengthening capacity for sub‐ and non‐state action; enabling accountability; and realizing sustainable development.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.841

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 head0.053
GPT teacher head0.290
Teacher spread0.237 · 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