An Assessment of How the Pandemic Affected the Cruise Tourism
Bibliographic record
Abstract
Cases of the Covid-19 pandemic around the world have been changing hourly since the beginning of 2020. Under the effect of the Covid-19 pandemic, negative impacts on the maritime trade and tourism are a sign of the economic impacts globally. Tourism and maritime sectors are directly affected by the pandemic. In this concept cruise, tourism is the intersection of both sectors. While the world economy goes into the recession by the pandemic, the sectoral situation of the cruise industry shows that even big companies started the year 2020 in a good financial situation, but in the second quarter of 2020, economic results of the adverse impacts are shown because of the voyage restrictions. The economic difficulties forced some businesses to sell their ships. All these impacts show that a return to pre-pandemic touristic activity levels before 2023 is impossible. This study aims to observe how the pandemic affected cruise tourism and which strategies can be implemented during and after the pandemic. In this sense, it is thought that cruise tourism must resume with sustainable solutions since it contributes significant values to both the country and business economics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".