Towards a new definition for “visiting friends and relatives”
Bibliographic record
Abstract
Abstract “Visiting friends and relatives” (VFR) is a tourism term used in academic and practitioner vernacular that refers to a substantial amount of activity and is yet commonly disregarded. This paper builds on previous literature that has demonstrated how a lack of understanding of what VFR encompasses facilitates the phenomenon to be undervalued and misunderstood. Without a clear conceptual definition, VFR continues to be presented with inconsistent and conflicting parameters, which creates discursive confusion rather than clarity and appreciation. This is important as tourism is often presented as a positive force for economic development in a wide range of communities, and VFR is almost routinely overlooked with high‐yield (hotel consuming) markets favoured; this is despite a growing body of literature that has explored the sustainability and positive community impacts of VFR activity and potential. A review of existing definitional work on VFR is provided, and a new conceptual definition is offered. Mobility influenced by a host is first distinguished from other forms of human movement; VFR is then positioned as a form of mobility influenced by a host that includes face‐to‐face interaction between a host and visitor who have a preexisting relationship. Implications for future research and practice are discussed.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".