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Record W3014001166 · doi:10.1002/aqc.3320

Characterizing tourism benefits associated with top‐predator conservation in coastal British Columbia

2020· article· en· W3014001166 on OpenAlexafffundabout
Rebecca Martone, Robin Naidoo, Theraesa Coyle, Bertine Stelzer, Kai M. A. Chan

Bibliographic record

VenueAquatic Conservation Marine and Freshwater Ecosystems · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsMinistry of ForestsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTourismOtterRevenueWildlifeEcotourismBusinessFisheryEnvironmental resource managementEcosystem servicesRecreationMarine ecosystemGeographyEnvironmental planningNatural resource economicsEcosystemEcologyEconomics

Abstract

fetched live from OpenAlex

Abstract Facing public concern over costs related to top‐predator reintroductions and conservation, ecosystem services such as ecotourism are often used to evoke benefits that outweigh or offset those costs. Quantifying these benefits using rigorous scientific methods can provide confidence to policymakers and other stakeholders that predators can in fact deliver positive outcomes to people living alongside them. The evaluation of these benefits is often anecdotal or qualitative, however, and empirical quantifications are rare. In coastal marine ecosystems, sea otter reintroduction is seen as a conservation success to some but a bane to others. The contribution of sea otters ( Enyhdra lutris ) to tourism revenue is touted as a crucial ecosystem service benefit to offset the loss of shellfish harvesting and associated revenue, but remains unquantified, weakening the favourable reception of conservation action. The potential economic benefits of sea otters associated with tourism and the extent to which benefits are realized were evaluated based on: (i) choice‐experiment surveys of tourists; and (ii) interviews with tourism operators in British Columbia. Sea otters were a strong factor in people's choices regarding wildlife viewing, and sea otters could have large benefits for local economies. Alongside socio‐economic characteristics, tourism experience influences tourists’ preferences. Tourism operators did not perceive sea otters as strongly influencing tourist choice, highlighting the gap that can occur between the perception and the reality of tourist preferences, leading to missed opportunities for the alignment of economic development with conservation actions.

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)0.000
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 score0.588
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.046
GPT teacher head0.177
Teacher spread0.131 · 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

Citations15
Published2020
Admission routes3
Has abstractyes

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