Bibliographic record
Abstract
Water is becoming one of the world's most crucial concerns. A third of the world's population has severe water shortage, while three quarters of the global population lives in deltas which run the risk of severe flooding. In addition, many more face problems of poor water quality. While it is apparent that drastic action should be taken, in reality, water problems are complex and not at all easy to resolve. There are many stakeholders involved - industries, local municipalities, farmers, the recreational sector, environmental organisations, and others - who all approach the problems and possible solutions differently. This requires delicate ways of governing multi-actor processes. This book approaches the concept of 'water management' from an interdisciplinary and non-technical, but governance orientation. It departs from the fragmented nature of water management, showing how these lack cooperation, joint responsibility and integration and instead argues that the capacity to connect to other domains, levels, scales, organizations and actors is of utmost importance. Connective capacity revolves around connecting arrangements (such as institutions), actors (for instance individuals) and approaches (such as instruments). These three carriers of connectedness can be applied to different focal points (the objects of fragmentation and integration in water management). The book distinguishes five different focal points: (1) government layers and levels; (2) sectors and domains; (3) time orientation of the long and the short term; (4) perceptions and actor frames; (5) public and private spheres. Each contributor pays attention to a specific combination of one focal point and one connective carrier. Bringing together case studies from countries including The Netherlands, United Kingdom, Romania, Sweden, Finland, Italy, India, Canada and the United States, the book focuses on the question of how to deal with the various sources of fragmentation in water governance by organizing meaningful connections and developing 'connective capacity'. In doing so, it provides useful scientific and practical insights into how 'connective capacity' in water governance can be enhanced.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".