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Record W1965340932 · doi:10.1080/13683500.2014.897688

Wild horse-based tourism as wildlife tourism: the wild horse as the other

2014· article· en· W1965340932 on OpenAlexaffabout
Claudia Notzke

Bibliographic record

VenueCurrent Issues in Tourism · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsTourismWildlifeWildlife tourismContext (archaeology)GeographyWildlife conservationRecreationWildlife managementPolitical scienceEnvironmental ethicsEcotourismEcologyArchaeologyBiology

Abstract

fetched live from OpenAlex

Wild horses as the focus of tourism occupy a unique position. This is a consequence of their ambiguous status in the natural and cultural landscape, particularly in North America. Wild horses are ecological agents, cultural icons, economic factors and political pawns. The complexity of their management environment has an impact on the tourism and recreational context. Focusing on the western US and western Canada, this article explores a conceptual framework for wild horse-based tourism and highlights unique characteristics of the encounter between wild horses and visitors, drawing on literature and empirical data. It positions wild horse-based tourism within a framework of wildlife tourism and introduces the wild horse as a charismatic animal which elicits strong reactions from visitors who encounter it. While visitors tend to embrace the wild horse as an integral part of its habitat, as a symbol of the western frontier, and an embodiment of freedom, the animal remains an extremely polarising subject in the management debate of public lands in the USA and Canada. The wild horse's beleaguered status in both countries seriously interferes with the realisation of the true potential of wild horse-based tourism. On the other hand, wild horse supporters pin high hopes on this industry's transformative power.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.013
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.349
Teacher spread0.322 · 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

Citations29
Published2014
Admission routes2
Has abstractyes

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