MétaCan
Menu
Back to cohort
Record W1561241939 · doi:10.7202/1036564ar

Innovative Community Tourism in Uganda

2012· article· en· W1561241939 on OpenAlexaff
Kelly J. MacKay, Jeffrey M. Campbell

Bibliographic record

VenueTéoros Revue de recherche en tourisme · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of ManitobaToronto Metropolitan University
Fundersnot available
KeywordsLivelihoodTourismLocal communityGeneral partnershipSustainabilityGorillaEconomic growthLocal DevelopmentBusinessCommunity developmentGeographyMarketingSocioeconomicsPolitical scienceRegional scienceSociologyAgricultureEconomicsFinanceEcology

Abstract

fetched live from OpenAlex

This paper illustrates an innovative approach to enhance rural livelihoods through community tourism in Uganda. Following pro-poor tourism principles of local participation and linking with existing systems, Gorilla Friends Tented Camp opened in Ruhija village, where mountain gorillas were recently habituated for gorilla tracking tours. In a village that had no previous tourist accommodations and few opportunities for villagers to earn income, a percentage of profits from Gorilla Friends Tented Camp are returned to support other livelihood enhancement initiatives in the village. While much of our previous research has focused on identifying and developing local capacity to participate meaningfully in Uganda’s tourism industry, attention must also be paid to tourists’ experiences at the site to ensure continued viability. Findings based on interviews with tourists to Ruhija illustrate the need for national partnership networks to support local community tourism. Additionally, understanding how tourists came to and experienced the community will assist the local people with sustainability of their operations and activities, and inform continued innovation in community tourism development in Ruhija.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.003
Scholarly communication0.0050.002
Open science0.0010.013
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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.

Opus teacher head0.317
GPT teacher head0.475
Teacher spread0.158 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueTéoros Revue de recherche en tourismeSame topicDiverse Aspects of Tourism ResearchFrench-language works237,207