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Rural Educational Tourism's Potential

2017· article· en· W4249189619 on OpenAlexaffvenueabout
Danielle Robinson

Bibliographic record

VenueRural Review Ontario Rural Planning Development and Policy · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsRural tourismTourismSustainabilityRural managementTourism geographyContext (archaeology)Economic growthRural areaBusinessPolitical scienceAgricultureGeographyRural developmentEconomics

Abstract

fetched live from OpenAlex

Growth trends in life-long learning, and rural tourism indicate potential for the rural educational tourism sector; however; there is very little empirical research on how this niche tourism, which may include activities such as, agricultural school excursions/exchange programmes, “farm-to-table” culinary courses, artisan craft programs, etc., might build local capacity, support sustainable rural economies, and mobilize place-based ways of learning that are required for global sustainability. This research project, which is at the conceptual/exploratory stage, aims to explore the economic, social and environmental impacts of rural educational tourism. There is no existing research that brings together rural development and place-based educational tourism in a Canadian context. Sub-questions with particular relevance to rural development policy and planning include: How was rural educational tourism integrated within a greater economic and learning development strategy? What new roles and competencies did stakeholders require and how were they developed? What changes from traditional forms of policy development were required? How were issues of sustainability, environmental impact, and conservation addressed? How did the quality and quantity of interconnections change? Since educational tourism has received very little research attention, comparative case studies with mixed methods are a suitable approach. I hope to include educational tourism activities in rural Aboriginal communities, pending consultation, and with an understanding of Aboriginal research as being research by and with Aboriginal Peoples. My approach emphasizes and values the existing strengths, assets and knowledge systems of rural communities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.335
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 teacher head, not a consensus.

Study designNot applicable
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
Published2017
Admission routes3
Has abstractyes

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