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Record W4405135722 · doi:10.22584/nr56.2024.009

Emergent and Regional: Networked Climate Governance Across Northern British Columbia

2024· article· en· W4405135722 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Northern Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversity of VictoriaUniversity of Northern British Columbia
FundersUniversity College London
KeywordsCorporate governanceGeographyClimate changeRegional sciencePolitical scienceEconomic geographyEnvironmental resource managementEnvironmental planningEcologyEnvironmental scienceBiologyEconomicsManagement

Abstract

fetched live from OpenAlex

Cities and municipalities have emerged as important actors in climate governance, building capacity and leverage through networks. City networks have led to increased agency for local governments at national and international scales but fail to represent northern, rural, and remote geographies. In response, the Northern British Columbia Climate Action Network (NorthCAN) emerged out of a desire to generate connections in the region and across public and private sectors. This research examined NorthCAN as a regional and multi-sector organization that has the goal of accelerating low-carbon transitions in northern British Columbia. It was informed by data collected via survey and qualitative interviews with active NorthCAN members. Our discussion explores the barriers and opportunities at play in this case of networked climate governance, while exploring equity, policy mobility, and community-centred transition as key themes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.030
GPT teacher head0.332
Teacher spread0.303 · 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