TOWARD A MODEL OF BALANCED TOURISM DEVELOPMENT ON BAFFIN ISLAND
Bibliographic record
Abstract
A desired outcome of indigenous tourism is culture- or nature-based experiences that hosts and guests are willing to accept and share. However, researchers warn there is a paradox between bringing new economic opportunities into a culture area and sustaining the local culture. This hybrid study investigates three research questions: (1) what forms of tourism have evolved during seven years of existence of Nunavut Territory where tourism is a new industry, the culture traditional, and the environment pristine; (2) how has tourism impacted hamlet life on Baffin Island; and ultimately, (3) how can research findings be utilized to guide tourism providers, marketers, visitors, and host hamlets to develop a product that is economically beneficial but does not undermine the environmental and cultural fabric of the region? This undertaking uses elements of both practitioner and academic research: analysis of the Nunavut Pleasure Traveler Exit Study; pre-visit and post-visit focus groups with first-time visitors to Arctic hamlets aboard the cruise ship MV Explorer; chronicled reflections of visitors to Arctic communities with a minimum of one prior hamlet experience; interviews with Nunavut Tourism, Parks Canada, as well as hamlet and Inuit cooperative officials; interviews of cruise ship operators; a literature search; and empirical observation of cultural and tourism landscapes in Kimmirut and Kinngait. This is the first stage of an on-going applied research effort.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".