Resilience and coping strategies against socio-ecological risks: a case of livelihoods in a Botswana rural community.
Bibliographic record
Abstract
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 --------------------------------------------------------------- Stratégies de résilience et d'adaptation face aux risques socio-écologiques: un cas de subsistance dans une communauté rurale du Botswana Résumé Devant l'éminence du développement durable (DD) comme cadre pour réagir aux risques socio-économiques dans les communautés, les risques ont plus de chance de perdurer pour les communautés rurales pauvres entrainant la baisse des bénéfices issus de ressources naturelles, ce qui est la base de leur subsistance. Et ceci malgré une promotion extensive des approches de gestion des ressources naturelles de la communauté qui ont été instaurées dans la dernière décennie pour réduire ces risques. De telles communautés peuvent être vues comme faisant parties de systèmes socio-écologiques mais peuvent s'effondrer davantage dans un état indésirable de risques socio-économiques lorsque les stratégies de résilience et d'adaptation sont manquantes au sein d'elles-mêmes. La survie des ces communautés peut parfois être complexe et coûteuse si elle n'est pas correctement gérée et supportée. À l'aide d'une étude de cas unique dans une communauté rurale pauvre de Chobe, nous illustrons en détail dans quelle mesure un individu de ces communautés rurales peut développer des stratégies de résilience et d'adaptation face aux risques socio-écologiques, dans le but de maintenir leur existence. Ceci est démontré en examinant l'initiative d'un forgeron du Botswana qui, à travers ses compétences de forgeron, a pu subvenir à ses besoins. Grâce aux entrevues et aux observations du cas, nous illustrons en détail que ce n'est pas seulement une forme de résilience et de développement de stratégie d'adaptation, mais aussi une opportunité pour la Gestion du Développement Naturel des Communautés (CBNRM en anglais) des schémas de DD auxquels contribuer ainsi que des initiatives dont il faut apprendre pour mieux améliorer la capacité de construire dans de telles communautés.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".