Reconsidering global mobility – distancing from mass cruise tourism in the aftermath of COVID-19
Bibliographic record
Abstract
The mass cruise tourism industry (MCTI) is inscribed in a neoliberal production of tourism space that promotes the economic, sociocultural and environmental marginalization of cruise destinations. With cruise tourism halted as a result of the COVID-19, but likely to resume in 2021, I question the relevance of this form of tourism and propose future development alternatives aligned with deglobalisation and degrowth of the industry. Power relations with destinations communities can be critiqued using the concepts of global mobility and local mobility to show that the former, imperative for the deployment of mass cruise tourism, is a weakness for the industry in a post-pandemic perspective of reduced mobility. Destinations must use the industry’s dependence on global mobility as leverage to transform the balance of power in their favor and promote local mobility. They must embrace radical solutions to take control of their territory to favor a transition from “Growth for development” to “Degrowth for liveability”. Host territories, relying on national and regional governance, should gradually ban or restrict the arrival of mega-cruise ships, implement policies that promote the development of a niche cruise tourism industry (NCTI) with small ships and develop a fleet controlled by local actors.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".