Bibliographic record
Abstract
COVID-19 pandemic outbreak caused slowdown of global tourism performance already in March 2020, followed by freefall in second quarter amid worldwide travel restrictions and lockdowns Tourism as the most important industry in Croatia has been seriously affected by pandemic related travel restrictions, with hotels facing the most serious decline year-on-year Usually tourists can autonomously choose where to travel and in other recent crisis events dominantly only some specific areas were affected During this pandemic there are no unaffected areas, but some regions and accommodation types are more resistant than the others Lower number of confirmed COVID-19 cases and gradual reopening of Croatia in summer months enabled partial rebound of tourism results in the country, however August brought new slowdown of foreign arrivals of such magnitude that higher number of domestic nights spent were not sufficient to compensate severe drop of tourist arrivals coming from other important tourism markets The goal of this paper is to analyse impact of COVID-19 pandemic on recent tourism results in Croatia, with breakdown by accommodation type, most important markets and local sub-regions Analysis of different outcome depending on this breakdown should indicate causes of more resistant areas and lead to some recommendations for advanced destination management
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".