Local institutional adaptation for sustainable water management under increasing climatic variability and change
Bibliographic record
Abstract
Purpose The study aims to explore institutional adaptation for sustainable water resources management at the local level in the context of increasing climate-related challenges in Zimbabwe using the case of a semi-arid area in the mid-Zambezi Valley, north of the country. Design/methodology/approach Inspired by the critical institutionalism approach, the study uses qualitative methods (i.e. key informant interviews, semi-structured interviews, community workshops and documentary review) to understand the role of different formal and informal water-related institutions vis-à-vis responding to climate-related challenges in the case study area, and how the identified institutions can improve their efforts in the context of national water and environmental policy and regulation frameworks. Thematic analysis was used for data analysis. Findings The study found that climatic challenges in the case study area, as in most of rural Africa, have raised the stakes in local water management with respect to regulating access to and balancing competing interests in, and demands for, water. It ultimately argues for the embracing of complexity thinking and flexibility in local water management as well as clear coordination of institutions across scales in the face of increasing climate-related challenges. Originality/value The study adds to case studies and evidence-based analyses focused on institutional alternatives for climate adaptation vis-à-vis water resources management in water-stressed rural African communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".