Enabling sustainable river futures: Exploring institutional interventions
Bibliographic record
Abstract
Increasing concern over deteriorating health of river systems has prompted a shift in river management practices from a technocratic ‘command-and-control’ focus towards notions of river repair. Key elements and principles of this emerging approach are encapsulated in ‘sustainable river management’, incorporating visionary, catchment-framed, ecosystem-based approaches through participatory and adaptive processes, couched within principles of integration, justice and place. While these ideas are firmly ingrained within the river management literature, management practice has not necessarily paralleled these trends. Governance frameworks underpinning management applications are key to enabling this transition. ‘Middle ground’ frameworks are considered to promote and enable sustainable river management, as they integrate ‘top-down’ and ‘bottom-up’ frameworks. This thesis seeks to provide a nuanced understanding of the precise structure, mechanisms and practices of middle ground governance frameworks. Geographical literature on environmental governance provides a lens for analysing governance frameworks, emphasising concerns for engagement with space and place. Notions of scale, nature-society coherence, adaptive governance and imagining, challenging and producing environmental futures embrace space and place concerns demonstrate how governance frameworks mediate dynamic relationships between nature and society. These themes provide an analytical framing of an inductive mixed-qualitative methods approach to examine the experience of three institutional interventions: Project Twin Streams in Auckland, New Zealand; the Grand River Conservation Authority in Ontario, Canada; and the Mersey Basin Campaign in North West England. Each of these interventions are internationally recognised for their success in undertaking sustainable river management practices, and together, their stories provide an understanding of the diversity and place-specific grounding of frameworks. Emerging from analysis, three key lessons underpin understandings of how middle ground governance frameworks support the emergence and continuance of sustainable river management practices. First, a diversity of governance spaces available for river management leads to diversity in the configuration of the middle ground. Secondly, disturbance and change within the political, socioeconomic and biophysical context of each catchment intervention render no ‘one grand narrative’ appropriate for the evolution of a given middle ground framework. Thirdly, the work which middle ground networks perform is more important than the configuration of the relationships themselves.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".