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Record W3130606495 · doi:10.1038/s42949-021-00015-z

Accelerating climate research and action in cities through advanced science-policy-practice partnerships

2021· article· en· W3130606495 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenpj Urban Sustainability · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsDalhousie University
FundersInternational Development Research Centre
KeywordsAction (physics)Promotion (chess)Work (physics)Political sciencePublic relationsScience policyClimate scienceKnowledge managementManagement scienceBusinessEngineering ethicsClimate changePublic administrationEngineeringComputer sciencePolitics

Abstract

fetched live from OpenAlex

Abstract Cities have become increasingly recognized as key sites for climate research and action. Recently, these efforts have been significantly advanced through science-policy-practice partnerships. The objective of this paper is to assess how these partnerships are structured, the research and action agenda that underpins them, and how this agenda is being articulated and implemented. The assessment also helps to define some of the conceptual and operational gaps faced by the science-policy-practice community and how they can be addressed. The work evaluates the critical conditions for promoting these advances including the definition and fulfillment of knowledge needs, the integration of different perspectives and approaches, establishment of pathways to finance the urban climate research and action community, and creation and promotion of new partnerships. The paper concludes with a series of strategies and recommendations for how targeted policy adjustments can accelerate and support the production of actionable knowledge and this integrated researcher-policymaker-practitioner community.

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)0.005
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.003
Scholarly communication0.0000.003
Open science0.0000.001
Research integrity0.0000.001
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 head0.163
GPT teacher head0.415
Teacher spread0.252 · 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