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Record W4402641020 · doi:10.7202/1113392ar

A Just Destination? Exploring Local Hopes, Fears, and Power Asymmetries in East Greenlandic (Tunu) Tourism Development

2023· article· en· W4402641020 on OpenAlexvenueno aff
Ulunnguaq Markussen, Carina Ren

Bibliographic record

VenueÉtudes/Inuit/Studies · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsTourismTourism geographyPower (physics)Sustainable developmentCultural heritageHeritage tourismPolitical scienceGeographyEconomyEconomic geographyEconomicsLaw

Abstract

fetched live from OpenAlex

This paper examines current actions towards tourism development in East Greenland (Tunu) and the expectations and concerns of locals in Tasiilaq, specifically regarding the possible inclusion of the East Greenlandic hunting culture on the UNESCO World Heritage List. We explore how locals see the potential and impact of the UNESCO recognition on tourism development in the region and its potential effects on local economy, culture, and traditions. Also discussed are the structural challenges faced by the local community as well as their aspirations for sustainable tourism development, unraveling the perception of power asymmetries and injustices between locals and outsiders and between East and West Greenland. The complex and often paradoxical relationship between heritage, cultural identity, and economic growth in tourism is highlighted, pointing to how general challenges and barriers in Greenlandic tourism development are further amplified and distorted in East Greenland. This suggests a need for greater tourism justice in developing all and not just parts of Greenland as a destination.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.195
GPT teacher head0.404
Teacher spread0.209 · 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.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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