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Record W6995879290

Policies, methods and tools for visitor management proceedings of the second International Conference on Monitoring and Management of Visitor Flows in Recreational and Protected Areas, June 16 20, 2004, Rovaniemi, Finland

2015· article· en· W6995879290 on OpenAlexfundno aff

Bibliographic record

VenueJukuri (Natural Resources Institute Finland (Luke)) · 2015
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsnot available
FundersRocky Mountain Research StationBiotieteiden ja Ympäristön Tutkimuksen ToimikuntaNational Park ServiceU.S. Forest ServiceBlekinge Tekniska HögskolaLakehead UniversityAcademy of FinlandKanton ZürichNational Research FoundationU.S. Department of Agriculture
KeywordsVisitor patternRecreationTourismWork (physics)Sustainability
DOInot available

Abstract

fetched live from OpenAlex

The second International Conference on Monitoring and Management of Visitor Flows in recreational and protected areas (MMV 2) -conference provided a forum for research presentations and for exchange of information and experience of managerial policies, problems, practices and solutions regarding issues related to monitoring and management of visitor flows in recreational and protected areas. These proceedings cover ten research topics, which were chosen to reflect current on-going research work internationally in the field of visitor monitoring and management. Monitoring visitor flows and also other types of recreational inventories are discussed in 16 articles and four posters on visitor monitoring methods, experiences of national, regional and on-site visitor inventories and visitor flow modeling and data management. Nineteen papers and three posters are discussing visitor management research from several perspectives. Articles related to issues of visitor conflicts, implementation of visitor information in management processes, different aspects of sustainability and carrying capacity issues in recreational settings make the largest group of papers. The third major subject group of articles (16) deal with visitor management policy issues, and nature tourism policies in recreational and protected areas. The last topics include economic and social impacts of recreation and nature tourism in the surroundings communities, regions and countries.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score0.952

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 head0.043
GPT teacher head0.347
Teacher spread0.304 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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