Developments in the tourism sector during the COVID-19 pandemic
Bibliographic record
Abstract
This box assesses the implications of the coronavirus (COVID-19) pandemic for the euro area tourism sector, trade in travel services and consumption of non-residents. Declining mobility during the pandemic has led to a slump in trade in services and tourism. As a result, the drop in non-resident consumption has acted as a shock amplification mechanism in countries exporting tourism services, i.e. countries which receive a lot of tourists, and as a shock absorption mechanism in countries importing tourism services. The partial recovery of tourism services observed during the summer months was mostly generated by domestic tourism substituting foreign tourism. The reintroduction of travel restrictions in October will likely imply that this substitution will continue to affect the dynamics of tourism services. High-frequency data on tourism, travel and services production point to a renewed overall deterioration of tourism services in the final quarter of 2020. JEL Classification: E01, E21, F14, Z3
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".