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Record W2004734270 · doi:10.12735/jotr.v1i1p51

Using Cultural Resources in Host Communities and the Environs to Enhance the Natural Resources Attractiveness of Ecotourism Development in Omo Biosphere Reserve (OBR), Nigeria

2014· article· en· W2004734270 on OpenAlexvenueno aff
O. K. Sonubi

Bibliographic record

VenueJournal of Tourism and Recreation · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsAttractivenessBiosphereNature reserveEcotourismNatural resourceHost (biology)GeographyNatural (archaeology)TourismEnvironmental resource managementBusinessEcologyEnvironmental scienceBiologyArchaeology

Abstract

fetched live from OpenAlex

The study was undertaken to evaluate the cultural resources in Omo Biosphere Reserve (OBR) host communities and its environs that can enhance the attractiveness of ecotourism development which can ultimately lead to the sustainable development of the area. OBR is in waterside area of Ogun State, Nigeria. It is a UNESCO designated Man and Biosphere (MAB) site. OBR natural resources has been under threat of overexploitation in the last few decades and hence the need to sustainably conserve and protect these resources using ecotourism. Fauna direct sighting particularly the large mammals like the forest elephants (Loxodonta africana cyclotis), forest buffalo (Syncerus caffer nanus) and others have been rare although their presence have been established. Interview and direct observation methods were used to collect primary data. Data collected were analysed and presented in tables. The result showed that there were significant festivals in OBR environs that can attract visitors to OBR. The study identified the incorporation of festivals in the OBR as added attractiveness for the natural resources in OBR in its ecotourism development. Development of ecotourism will not only conserve the endangered fauna and flora species of Omo Biosphere Reserve but will also provide additional income and job opportunities for the communities and will equally ensure peaceful co-existence of the people.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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