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The Impact of Rural Tourism on Wellbeing

2019· book-chapter· en· W3157459946 on OpenAlexaboutno aff
Alina-Cerasela Aluculesei

Bibliographic record

VenueAdvances in hospitality, tourism and the services industry (AHTSI) book series · 2019
Typebook-chapter
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsTourismDynamismRural tourismTourism geographyRural areaGeographyRegional scienceBusinessEconomic growthEnvironmental planningPolitical scienceEconomics

Abstract

fetched live from OpenAlex

This chapter aims to enhance general knowledge about the impact of rural tourism on the wellbeing in a country that is known to have an impressive potential both on spa and rural tourism. The approach will take into consideration the new profile of tourists in recent years and the dynamism of the tourism field in Europe. Based on the research that the author has made in recent years on health tourism and wellbeing, expanding the scientific approach to the rural area represents the next step in her approach, given the potential of this field in Romania. The chapter will address the ways of capitalising on the rural tourism resources in Romania through the specific activities of the concept of “rural wellbeing tourism.” This model has been successfully developed and implemented in the Nordic countries, Austria, Switzerland, Iceland, and Canada, and it is considered a way to generate highly competitive tourism products.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.736
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.363
Teacher spread0.349 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations1
Published2019
Admission routes1
Has abstractyes

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