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From Birds to Boats: The Political Ecology of Cruise Tourism in Mingan Archipelago National Park Reserve in Quebec (canada)

2018· article· en· W2907068029 on OpenAlexaboutno aff
Jonathan Tardif, Robin Roth

Bibliographic record

VenueTourism in Marine Environments · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCruiseTourismWildernessDestinationsArchipelagoPoliticsNational parkAdventurePolitical ecologyRevenueRecreationWilderness areaEnvironmental resource managementPolitical scienceGeographyEcologyBusinessEconomicsEngineeringArchaeologyFinance

Abstract

fetched live from OpenAlex

Driven by spectacular growth over the last decade, the international cruise industry is constantly looking for new destinations to appeal to a different breed of traveler, one that seeks comfort alongside wilderness adventure. Meanwhile, national parks, long held up as icons of wilderness adventure, are increasingly governed through the logic of austerity politics and seek new revenue. These two distinct processes have started to provide increased opportunities for collaboration, introducing complex dynamics and power struggles at destinations and beyond. However, few studies have addressed these issues so far. Drawing on the global political ecology of tourism and conservation literature, this article examines the various entanglements between Mingan Archipelago National Park Reserve in Canada and the cruise industry, and the implications they have for the destination as a whole. To better understand the many challenges facing park authorities and their partners, we employed a slate of qualitative methods, including document analysis, participant observation, and 30 semistructured interviews with key stakeholders. Results show that although the expectations of regional actors have not been met and the future of cruise tourism in Mingan is uncertain, park authorities continue to invest time and money to engage with the industry and adapt their facilities to this clientele. This raises questions about the real motives of park authorities and the contribution of this form of tourism to the sustainable development of the region.

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)0.001
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 score0.037
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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
Published2018
Admission routes1
Has abstractyes

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