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Record W3011191530 · doi:10.5539/sar.v9n2p74

Promoting Sustainable Development in Rural Communities: The Role of the University of Botswana

2020· article· en· W3011191530 on OpenAlexvenueno aff
Flora Tladi-Sekgwama, Gabo Peggy Ntseane

Bibliographic record

VenueSustainable Agriculture Research · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityLivelihoodNatural resource managementCommunity engagementCommunity developmentSustainable developmentRural developmentPolitical scienceSustainable communityNatural resourceEnvironmental resource managementBusinessEnvironmental planningPublic relationsGeographyAgricultureEconomicsEcology

Abstract

fetched live from OpenAlex

Universities are better placed through their community engagement mandates to provide solutions for sustainable community livelihoods. The paper uses the case of the Community Based Natural Resource Management (CBNRM) strategy, regarded as both a conservation and rural development strategy in Botswana to demonstrate how a structured community engagement agenda can enable the University of Botswana to play a more impactful role in the successful implementation of nationally upheld development initiatives such as the CBNRM. Systems theory is applied to demonstrate the need for a university engagement strategy, working model, guide to CBNRM sustainable development activities and a framework for the maintenance of sustainable engagement partnerships. Literature review showed uncoordinated research activity in support of the CBNRM by different departments and institutes of the UB. While content analysis of the CBNRM draft policy objectives showed the UB being more impactful by focusing its community engagement on two modes: “sustainability partnerships” and “research committed to sustainability”.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.228
Teacher spread0.209 · 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 designQualitative
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
Published2020
Admission routes1
Has abstractyes

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