Last-chance tourism: the boom, doom, and gloom of visiting vanishing destinations
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.
Bibliographic record
Abstract
Popular press and industry stakeholders are reporting a travel trend whereby tourists increasingly seek to experience the world's most endangered sites before they vanish or are irrevocably transformed. Termed ‘last-chance’ or ‘doom’ tourism in the popular media, the desire for tourists to witness vanishing landscapes or seascapes and disappearing species may have important consequences for tourism management, yet the nature of these consequences is poorly understood by the academic community. This paper describes how last-chance tourism is promoted in various tourism marketing strategies, especially in the Arctic. The analysis is supported through a literature review of web-based information and an analysis of three different studies conducted in Churchill, Manitoba, Canada – the self-declared polar bear capital of the world. The authors also examine more closely the concepts of dark and last-chance tourism, and elaborate on the possible connections between the two. The paper concludes with a discussion of the implications of this type of tourism and identifies potential risks and opportunities.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it