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Record W4386212710 · doi:10.32920/24043557.v1

The Connection Between Cultural Tourism and Visiting Friends and Relatives (VFR) Tourism from Immigrant Hosts' Perspectives

2023· preprint· en· W4386212710 on OpenAlexaff
Md Wahidur Rahman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTourismImmigrationTourism geographyGrounded theorySociologyMarketingGeographyBusinessQualitative researchSocial science

Abstract

fetched live from OpenAlex

The objective of this study is to discover and discuss the link between cultural tourism and VFR tourism from immigrant hosts’ perspectives. The grounded theory approach is applied, and a theoretical sampling technique is used for data collection and analysis. The data have been collected from Bangladeshi origin adult immigrants living in GTA. The study has found that hosts influence their VFR travelers in their visits and exploration of destination, practices and behaviour of people and their way of living. The result has also showed that the exploration of culture and the influence of hosts may turn their VFR travelers to cultural tourists. Finally, the study proposes a VFR-Cultural tourism continuum to explore the transition from VFR tourism to Cultural tourism and vice-versa. The study findings have practical significance as VFRs can be a unique form of travelers particularly after the COVID-19 situation, the visitors may likely make social connections and VFR tourism may act as a strategic alternative to tourism recovery.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.360
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2023
Admission routes1
Has abstractyes

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