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Record W2030666299 · doi:10.4236/ojf.2015.54033

Recreational Access Management Planning: Understanding Perceptions Regarding Public Forest Lands in SW Alberta

2015· article· en· W2030666299 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

VenueOpen Journal of Forestry · 2015
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsMount Royal UniversityUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of CanadaMount Royal UniversityUniversity of Calgary
KeywordsRecreationVisitor patternBusinessEnvironmental resource managementDistribution (mathematics)Forest managementEnforcementQuality (philosophy)Environmental planningMarketingGeographyEcologyForestryComputer science

Abstract

fetched live from OpenAlex

Management of recreational access on public forest lands is a complex issue of growing global importance. The provision of public recreation opportunities is part of the suite of ecological goods and services that must be considered by many forest managers. Effective access management is predicated on understanding the attitudes and perceptions of recreation users in order to predict and influence visitor behaviour and gauge the acceptance of new management strategies. Potential access management strategies vary given the nature of recreation activities and include: restricting the amount, type, and spatial distribution of use, visitor education, temporal restrictions and enhancing site durability. In this research we examined the views of recreation users on public lands in southwestern Alberta, Canada through implementation of an online survey (n = 945) with a focus on access management options. The results indicate a strong belief that the quality of the recreation experience is declining and that increased management and enforcement are required. More detailed analysis indicates that demographic and user-type variables strongly influence ideas about appropriate management. Forest managers need to engage with, understand, and respond to a wide variety of recreation user needs and preferences.

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)0.001
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: none
Teacher disagreement score0.517
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.000
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 head0.288
GPT teacher head0.430
Teacher spread0.143 · 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