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Record W2274296455 · doi:10.1177/0263774x15614675

Lament for a network? Cities and networked climate governance in Canada

2015· article· en· W2274296455 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironment and Planning C Government and Policy · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
Fundersnot available
KeywordsCorporate governanceExtant taxonPolitical scienceCoercion (linguistics)Collective actionNetwork governanceService (business)Public relationsPublic administrationBusinessPoliticsLawMarketing

Abstract

fetched live from OpenAlex

There is substantial evidence that the global governance of climate change must pass through cities. While formal networks offer cities a means of generating effects that extend beyond their own borders, it remains unclear as to whether such networks can address collective action barriers and implementation gaps. City-networks, after all, are limited in their efforts to govern and must rely on information, service provision, and soft forms of coercion if they are to steer their members past these considerable challenges. This article contributes to extant efforts to assess their ability to do so by addressing two gaps in the literature. First, the article focuses on the Partners for Climate Protection (PCP), a city-network that has received little attention to date. Second, through analysis of two Canadian cities (Toronto and Winnipeg), the article provides an empirical illustration of the limitations of network authority and influence, and offers some thoughts on what this means for networked urban climate governance in Canada and beyond.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score0.813

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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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