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Record W2287559686 · doi:10.1080/14927713.2015.1074401

The role of tour operators in delivering a Leave No Trace program: a case study of Algonquin Provincial Park

2015· article· en· W2287559686 on OpenAlexaffvenueabout
Lauren J. King

Bibliographic record

VenueLeisure/Loisir · 2015
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsVisitor patternChristian ministryGeographyEnvironmental protectionEnvironmental resource managementEnvironmental planningPolitical scienceEnvironmental science

Abstract

fetched live from OpenAlex

The first State of Ontario’s Protected Area Report identified visitor impacts as one of the known threats to the maintenance of ecological integrity in Ontario’s provincial parks (Ontario Ministry of Natural Resources, 2011b). To mitigate these impacts, Algonquin Provincial Park’s management adopted a Leave No Trace (LNT) program in spring 2011, a precedent-setting decision among provincial parks in Ontario (Algonquin Backcountry Recreationalists, 2011). This study examines what role, if any, tour operators in Algonquin Provincial Park play as delivery agents of an LNT program. Through the use of interviews and participant observation, the findings of this case study reveal that tour guides’ knowledge and use of an LNT program vary significantly. Recommendations to enhance tour operators’ role in delivering an LNT program and their effectiveness as environmental educators are discussed.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.751

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.030
GPT teacher head0.322
Teacher spread0.292 · 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 designQualitative
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

Citations3
Published2015
Admission routes3
Has abstractyes

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