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Record W7044140212

VFR turismens betydelse : Studenternas betydelse på antalet VFR turister i Umeå

2021· other· en· W7044140212 on OpenAlexaboutno aff

Bibliographic record

VenueDiVA at Umeå University (Umeå University) · 2021
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Affect (linguistics)Function (biology)Quarter (Canadian coin)Friendship
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.357
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.187
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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