What Might Brexit Mean for British Tourists Travelling to the Rest of Europe?
Bibliographic record
Abstract
Brexit will have profound implications for British tourists visiting the rest of the European Union, in particular because of the likely loss of coverage of healthcare should they be injured or fall ill. This paper compares the cost of travel insurance within the EU and in comparable countries outside it, asking how it varies by age and pre-existing conditions. Fictitious patients, differing by age, pre-existing condition, and destination (France, an EU Member State; Israel and Canada, two high income non-EU frequent destinations) were entered into an insurance price comparison website to assess the influence of these characteristics on prices quoted. Cost of travel insurance increases with age, pre-existing health conditions and by destination. In those with no pre-existing conditions, there is a marked difference between France, where the cost rises steadily with age, and Israel and Canada, where there is a sharp increase after age 75. For individuals with any one pre-existing condition, there is no similar jump in cost but rather a progressive increase with age, although the rate of increase accelerates as the individuals concerned get older. For all travellers, the cost of insurance is highest for Canada and lowest for France. At present, pre-existing health conditions in British tourists travelling in the rest of the EU are covered by the European Health Insurance Card. With the UK's probable exit from the EU and almost certain loss of this coverage, travellers in the older age groups may have to pay much more for their travel insurance, with some possibly tempted to forgo travel insurance coverage because of the cost. It is essential that health professionals understand how leaving the EU may impact on those seeking their advice.
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.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".