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Record W2910813904

Resilience and coping strategies against socio-ecological risks: a case of livelihoods in a Botswana rural community.

2018· article· en· W2910813904 on OpenAlexvenueno aff
Nthalivi Silo, Sinvula Serome

Bibliographic record

VenueJournal of rural and community development · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsLivelihoodCoping (psychology)Natural resourceNatural resource managementEnvironmental resource managementCommunity resiliencePsychological resilienceEnvironmental planningEcological resilienceBusinessGeographyEconomic growthPolitical scienceResource (disambiguation)PsychologyEconomicsAgricultureSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

With the eminence of sustainable development (SD) as a framework for responding to socio-ecological risks in communities, the risks are likely to persist for poor rural communities resulting from diminishing benefits from their natural resource base on which their livelihoods are sustained. This is in spite of the extensive promotion of community natural resource management approaches that have taken place in the past decade to alleviate these risks. Such communities can be viewed as part of socio-ecological systems that, when resilience and coping strategies are lacking within them, can collapse further into an undesirable state of socio-economic risks. The survival of these communities can sometimes be complex and costly if not properly managed and supported. Using a single case study in a poor rural community in Chobe, we further illustrate how an individual in these rural communities can develop resilience and coping strategies in the face of impending socio-ecological risks, to sustain their livelihood. This is demonstrated by examining the initiative of a blacksmith in Botswana, who through his blacksmith skills has been able to sustain himself. Through interviews and observations from the case, we further illustrate that not only is this a form of resilience and development of coping strategies, but also an opportunity for Community Natural Development Management (CBNRM) SD schemes to contribute to, and indeed learn from such initiatives to further enhance capacity building in such communities. Keywords: Resilience, coping strategies, CBNRM, socio-ecological risks, natural resources, livelihoods interest --------------------------------------------------------------- Strategies de resilience et d'adaptation face aux risques socio-ecologiques: un cas de subsistance dans une communaute rurale du Botswana Resume Devant l'eminence du developpement durable (DD) comme cadre pour reagir aux risques socio-economiques dans les communautes, les risques ont plus de chance de perdurer pour les communautes rurales pauvres entrainant la baisse des benefices issus de ressources naturelles, ce qui est la base de leur subsistance. Et ceci malgre une promotion extensive des approches de gestion des ressources naturelles de la communaute qui ont ete instaurees dans la derniere decennie pour reduire ces risques. De telles communautes peuvent etre vues comme faisant parties de systemes socio-ecologiques mais peuvent s'effondrer davantage dans un etat indesirable de risques socio-economiques lorsque les strategies de resilience et d'adaptation sont manquantes au sein d'elles-memes. La survie des ces communautes peut parfois etre complexe et couteuse si elle n'est pas correctement geree et supportee. A l'aide d'une etude de cas unique dans une communaute rurale pauvre de Chobe, nous illustrons en detail dans quelle mesure un individu de ces communautes rurales peut developper des strategies de resilience et d'adaptation face aux risques socio-ecologiques, dans le but de maintenir leur existence. Ceci est demontre en examinant l'initiative d'un forgeron du Botswana qui, a travers ses competences de forgeron, a pu subvenir a ses besoins. Grâce aux entrevues et aux observations du cas, nous illustrons en detail que ce n'est pas seulement une forme de resilience et de developpement de strategie d'adaptation, mais aussi une opportunite pour la Gestion du Developpement Naturel des Communautes (CBNRM en anglais) des schemas de DD auxquels contribuer ainsi que des initiatives dont il faut apprendre pour mieux ameliorer la capacite de construire dans de telles communautes.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.044
GPT teacher head0.300
Teacher spread0.256 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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