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Record W4402389739 · doi:10.1016/j.jort.2024.100818

Not seeing the wood for the (invasive) trees: Visitors’ perceptions of invasive wilding conifers in the New Zealand landscape

2024· article· en· W4402389739 on OpenAlexaff
Brent Lovelock, Yuejiao Ji, Anna Carr, Clara-Jane Blye

Bibliographic record

VenueJournal of Outdoor Recreation and Tourism · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsUniversity of Alberta
FundersUniversity of Otago
KeywordsInvasive speciesRecreationGeographyPerceptionLoggingAgroforestryEcologyForestryPsychologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Currently we know little about how visitors perceive invasive species, nor how this may vary across visitor cohorts. Previous research suggests that visitors to natural areas have a low awareness of the impact of invasive species. This note reports on a survey of domestic and international visitors (n = 231) in New Zealand, investigating their awareness of invasive wild conifers and attitudes toward their control. Awareness of the wild conifer problem was generally low, especially among international visitors. There were significant differences between domestic and international visitors, and among visitors of different nationalities for how wild conifers were perceived. International visitors, and particularly those from China or other Asian countries were more accepting of wild conifers in the landscape and less supportive of eradication. The findings have implications for management of invasive species, which requires the support of all stakeholders, including tourists, recreationists and their associated sectors.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.166

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 head0.018
GPT teacher head0.273
Teacher spread0.256 · 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
Published2024
Admission routes1
Has abstractyes

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