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Record W2045682424 · doi:10.5558/tfc82416-3

A national portrait of community forestry on public land in Canada

2006· article· en· W2045682424 on OpenAlexafffundvenueabout
Sara Teitelbaum, Tom Beckley, Solange Nadeau

Bibliographic record

VenueThe Forestry Chronicle · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceUniversity of New Brunswick
FundersCanadian Forest ServiceU.S. Forest Service
KeywordsPublic landCommunity forestryGovernment (linguistics)Local governmentForest managementCorporate governanceForestryLand managementEnvironmental resource managementGeographyBusinessPublic administrationEnvironmental planningLand usePolitical scienceFinanceEcologyEconomics

Abstract

fetched live from OpenAlex

Despite the interest community forestry generates, there is little published literature on the array of initiatives currently taking place across Canada. This paper presents the results of nationwide survey of community forestry initiatives on public land. The survey focused on basic characteristics such as objectives, organizational structures, and tenure types. The research revealed that there are over one hundred community forest initiatives currently taking place on public land, mainly in Ontario, Quebec, and British Columbia. Most of them are run through local government organizations. Approximately 60% operate on Crown land while the remaining 40% operate on land owned fee simple by local governments. The median land base is 4200 ha. The average age of community forests is 10 years. Key words: community forestry, community-based management, public participation, local governance, forest management organizations, Canada

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score1.000

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)0.0010.000

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 head0.016
GPT teacher head0.225
Teacher spread0.209 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations55
Published2006
Admission routes4
Has abstractyes

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