Applying the Concept of Fit to Water Governance Reforms in South Africa
Bibliographic record
Abstract
The call for a spatial fit between institutional arrangements and the resource they manage is reflected in such water management paradigms as river basin management and in a number of international agreements (e.g., the European Union Water Framework Directive). Consequently, a number of countries are currently introducing river basin management, which, besides management along hydrological boundaries, has recently come to include such aspects of governance as stakeholder participation and policy integration. Beginning with a discussion of the goals and limitations of river basin management, this paper describes how the concept has been implemented in South Africa-a country that has been lauded for its state-of-the-art water legislation, but whose water administration is currently struggling to implement it. The example begins by showing the limitations of focusing on the dimension of spatial fit: a perfect spatial fit in basin management is almost impossible owing to the nature of the resource and to social and economic requirements. There are trade-offs between the identification of hydrological boundaries (which sometimes proves difficult) and "boundaries" of social organization, such as a feasible size for effective management, meaningful stakeholder participation, and financial viability. Furthermore, the improved spatial fit of the institutional arrangement and water resource boundaries causes problems of interplay by increasing the need for coordination and cooperation among water management organizations at different levels and on different scales. The example then considers the relevance of other dimensions of water management. It shows that, besides the focus on spatial fit, there is a need to recognize major defining features or boundaries to the problem other than hydrological boundaries, such as those imposed by water service infrastructure (functional fit) and impacts of climate change (dynamic fit), and a need to acknowledge the political and economic dimensions of water management.
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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 | 0.000 | 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 | 0.000 |
| 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".