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Record W2991194215 · doi:10.1002/eet.1873

Local impacts of federal forest policy changes on Canadian model forests: An institutional capacity perspective

2019· article· en· W2991194215 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironmental Policy and Governance · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of SaskatchewanUniversity of Winnipeg
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsContext (archaeology)Local governmentForest managementVisionEnvironmental resource managementCorporate governanceBusinessOrder (exchange)Sustainable forest managementPublic administrationPolitical scienceForestrySociologyEconomicsGeography

Abstract

fetched live from OpenAlex

Abstract Although research in multiparty environmental governance has examined how local actors work together, few have focused how changes in higher order government policy directives affect the capacity of local organizations to implement associated management activities over time. We examine changes in three Canadian Model Forests as federal policy objectives shifted from “sustainable forest management” to “sustaining communities.” Specially, we adopt the concept of institutional capacity from planning theory to assess changes in knowledge resources, relational resources, and mobilization potential of Model Forest sites during the shift from the Model Forest Programme to the Forest Communities Programme. Analysis of key documents shows that despite being developed as a top‐down programme, individual sites exhibited an array of responses by drawing on local actors with new skills, political acumen, and relational resources to generate local opportunities. Although overall federal support decreased, Model Forest sites fostered collaborations with new sectors, enabling them to link ideas, resources, and influence in new ways and respond to changes they observed in the local context. Local networks created under a federal programme were able to move forward, shift their organizational identity, change visions, and initiate alternative projects after the programme stopped.

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 score0.516
Threshold uncertainty score0.951

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 studies0.0000.001
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 head0.009
GPT teacher head0.222
Teacher spread0.212 · 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