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Record W2112082674 · doi:10.1080/14693062.2007.9685636

Coordinating future adaptation policies across Canadian natural resources

2007· article· en· W2112082674 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

VenueClimate Policy · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGovernment (linguistics)AgricultureBusinessAdaptation (eye)Action (physics)Climate changePublic policyClimate change adaptationEnvironmental resource managementPolitical sciencePublic economicsEconomic growthEconomicsGeographyEcology

Abstract

fetched live from OpenAlex

What are the roles of informal coordination networks, policy-oriented beliefs, and the concern about climate change? Informal networks are considered in addition to the highly publicized strategies and commitments made by government departments and agencies. Based on a survey of agriculture, forestry and water-based policy elites in the Canadian prairies, this article examines the structure and impact of informal networks and policy-oriented beliefs. To do so, a number of testable hypotheses were proposed. The results indicate that respondents looked to the federal government as a potential ally. However, the federal government did not reciprocate by supporting the other major organizational clusters (agriculture and forest industry, provincial government, environment groups and research organizations). A bleak picture of future action on climate change emerges when the gaps between closed and polarized networks are considered.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.012
GPT teacher head0.284
Teacher spread0.272 · 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