The role of communities in integrated water resource management
Bibliographic record
Abstract
Since its first applications in river valleys in the 1930s, integrated water resources management (IWRM) has become a widely applicable holistic approach for water governance, resting on the key balance of economic, environmental and social aspects. This chapter discusses the history and key components of IWRM. Stakeholder engagement, one such key component, is an ambitious endeavour that requires special consideration to ensure that engagement is equitable and adapted to local contexts. Accordingly, participatory coupled human-water systems modelling and game-based approaches can engage stakeholders’ knowledge to create shared representations of reality. Citizen science and distributed databases also offer opportunities for more direct and sovereign involvement of communities in the IWRM process. Overall, this chapter explores the potential of IWRM to expand collaborative governance in water management strategies, providing an overview of innovative and emerging ideas and tools in this space to be used as a starting point for those interested in exploring different ways of engaging and empowering local communities through resource management.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".