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Record W1965526549 · doi:10.5558/tfc84210-2

Outdoor recreation participation in BC forest-dependent communities

2008· article· en· W1965526549 on OpenAlexafffundvenue
Howard W. Harshaw

Bibliographic record

VenueThe Forestry Chronicle · 2008
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaLakehead University
KeywordsRecreationEnvironmental planningForest managementEnvironmental resource managementBusinessGeographyForestryEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

Understanding recreation behaviour can help forest managers identify public uses of forests and gauge the extent of recreation use. This paper documents recreation behaviour in nine forest-dependent communities in British Columbia and examines three questions: (1) is outdoor recreation relevant to local residents?; (2) what are the characteristics of outdoor recreation participation?; and (3) are local residents satisfied with outdoor recreation forest management outcomes and land-use planning processes? Involvement in recreation activities was varied and longstanding. Non-motorized and motorized recreation played important roles as people’s main connection to forests. Knowing about recreationists’ satisfaction with land-use planning outcomes can help forest managers assess their success in meeting land-use objectives, and may help alleviate uncertainties in forest planning and management by reducing conflict, improving quality-of-life, and contributing to the social license of forestry activities. Key words: forest recreation; sustainable forest management; recreation participation

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.349
Threshold uncertainty score0.702

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.336
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2008
Admission routes3
Has abstractyes

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