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Record W4390672933 · doi:10.3390/land13010069

The Impacts of Climate Change on Tourism Operators, Trail Experience and Land Use Management in British Columbia’s Backcountry

2024· article· en· W4390672933 on OpenAlexaffabout
Courtney W. Mason, Pate Neumann

Bibliographic record

VenueLand · 2024
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsRecreationTourismEnvironmental resource managementGeographyClimate changeEnvironmental planningCitizen journalismPolitical scienceEcologyEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

Climate change, natural resource industries, and an expanding outdoor tourism sector have recently increased access to sensitive backcountry environments in Western Canada. Trail managers are struggling to manage trail conditions with the mounting effects of smoke, dust, fire, flood, area closures, and beetle outbreaks in their regions. Outdoor recreation trail managers are linking these events and are thinking critically about the history and interconnectedness of land use management decisions in the province of British Columbia (BC). As the effects of climate change continue to challenge both trail managers and sport recreationists, guides and trail associations have been identified as key education facilitators in the development and dissemination of environmental consciousness. Guided by a community-based participatory research approach, this study used personal interviews with trail managers across the province to highlight how a connection with local ecosystems can develop a more robust land ethic for recreational trail user communities in BC.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.033
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0030.000
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.295
Teacher spread0.273 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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