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Benevolent and Benign? Using Environmental Justice to Investigate Waste‐related Impacts of Ecotourism in Destination Communities

2009· article· en· W2073299662 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAntipode · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsUniversity of Northern British Columbia
FundersUniversity of Cape TownUniversity of Cambridge
KeywordsEcotourismTourismDiversification (marketing strategy)Service (business)HospitalityBusinessEnvironmental justiceEnvironmental planningEnvironmental resource managementMarketingPolitical scienceGeographyEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract: We contribute to the diversification of environmental justice (EJ) by using it to frame ecotourism‐related solid waste management problems. Ecotourism is a service industry portrayed as benevolent (providing benefits), and benign (reducing negative impacts). We propose four characteristics shared by ecotourism‐based communities in the Global South and communities struggling with more conventional EJ conflicts. We apply these characteristics to the solid waste crisis in Tortuguero, Costa Rica, a renowned ecotourism destination. First, we show that, despite their general absences from the EJ literature, service industries such as tourism and hospitality can create environmental injustices that disproportionately impact certain types of communities. Second, we highlight the roles of location and socio‐economic marginality in siting ecotourism development, in complicating related environmental impact management, and in limiting local abilities to respond to environmental management shortcomings. Third, we provide an example of opportunities to introduce EJ concepts and theory into the study of tourism.

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.

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 score0.253
Threshold uncertainty score0.691

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)0.0000.000

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 head0.028
GPT teacher head0.311
Teacher spread0.284 · 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