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Record W2195692014 · doi:10.22230/jem.2007v8n2a514

Governance and management of small forest tenures in British Columbia

2007· article· en· W2195692014 on OpenAlexaffabout
Stephen Tyler, Lisa Ambus, D'Arcy Davis-Case

Bibliographic record

VenueJournal of Ecosystems and Management · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsVancouver Community CollegeArbutus Biopharma (Canada)
Fundersnot available
KeywordsAccountabilityBusinessCorporate governanceAutonomyForest managementScope (computer science)DecentralizationLocal governmentLocal communityGovernment (linguistics)Environmental resource managementPublic administrationEnvironmental planningForestryPolitical scienceFinanceEconomicsGeography

Abstract

fetched live from OpenAlex

The growing number of small tenures in British Columbia creates new demands on local organizations to manage public forest lands. To deal with these demands, small tenure holders must develop governance practices that address both accountability and participation. Local participation is especially important for Community Forest Agreement (CFA) holders to ensure that community members are actively involved in decision-making processes. Both cfas and Woodlot licensees have upward accountability to the B.C. Ministry of Forests and Range. Holders of CFAs also have downward accountability to members of the local community. Community forests in the province have adopted various legal structures. Private corporations owned by local government are popular vehicles to hold CFAs and have commercial advantages, but their structure is less accountable than others. Although it is important to separate the political decisions of community forest governance from the technical decisions of management, both are needed. Experience with small tenures in other countries suggests that scope exists for sustainable, commercial forest management based on a substantial degree of local autonomy, if accompanied by technical support and oversight from governments, as well as training, extension, and services from voluntary associations of local tenure holders. Further study of options and experience with local forest governance and management will be helpful for small tenures in British Columbia.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.995

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 studies0.0000.000
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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2007
Admission routes2
Has abstractyes

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