VFR turismens betydelse : Studenternas betydelse på antalet VFR turister i Umeå
Bibliographic record
Abstract
Visiting friends and relatives is one of the oldest reasons for travelling. This form of travel is a way for friends and relatives to stay connected even if they live in different cities orcountries. Visiting Friends and Relatives, also called VFR tourism, is still important today. Even though some studies have been made in Australia, Germany, and Great Britain there is still a lack of research in other parts of the world. This means that this form of research is stillnecessary, especially in the northern countries. This study will contribute with a Swedish perspective by examining weather students at Umeå University received visits from friends and relatives during their time of study. The aim of this paper is to analyze how the presents of students affect the numbers of VFR tourists. A survey containing questions about visiting friends and relatives, activities and the students and their visitor’s behaviour during these visits was used to investigate this correlation. The result showed that the relationship between VFR tourists and students can be linked to migration. When students move, they function as a link between their old and new homeswhich is shown when friends and relatives choose to travel to visit them. The result also shows that students behave a bit differently during these visits and experience things that would not have experienced otherwise.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.128 | 0.038 |
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".