The evolution and performance of river basin management in the Murray-Darling Basin
Bibliographic record
Abstract
We explore bioregional management in the Murray-Darling Basin (MDB) in Australia through the institutional design characteristics of the MDB River Basin Organization (RBO), the actors and organizations who supported and resisted the establishment of the RBO, and the effectiveness of the RBO.During the last 25 years, there has been a major structural reform in the MDB RBO, which has changed from an interstate coordinating body to an Australian government agency.Responsibility for basin management has been centralized under the leadership of the Australian government, and a comprehensive integrated Basin plan has been adopted.The driving forces for this centralization include national policy to restore river basins to sustainable levels of extraction, state government difficulties in reversing overallocation of water entitlements, the millennium drought and its effects, political expediency on the part of the Australian government and state governments, and a major injection of Australian government funding.The increasing hierarchy and centralization of the MDB RBO does not follow a general trend toward multilevel participative governance of RBOs, but decentralization should not be overstated because of the special circumstances at the time of the centralization and the continuing existence of some decentralized elements, such as catchment water plans, land use planning, and water quality.Further swings in the centralization-decentralization pendulum could occur.The MDB reform has succeeded in rebalancing Basin water allocations, including an allocation for the environment and reduced diversion limits.There are some longer term risks to the implementation of reform, including lack of cooperation by state governments, vertical coordination difficulties, and perceived reductions in the accountability and legitimacy of reform at the local level.If implementation of the Basin plan is diverted or delayed, a new institution, the Commonwealth Environmental Water Holder, can play a major role in securing and coordinating environmental water supplies.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".