Smart Water Governance in Moroccan Agriculture: New Science and Policy Collaboration and Partnership
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The emergence of concepts like integrated water resources management and river basin management should be seen in the light of the governance transformation. The full potential of the governance transformation for improved management of water resources and services is yet to be fully realized. The general objective of this research was set to contribute to achieving SDGs related to water (SDG6), gender equality (SDG5), livelihoods and nutrition (SDG2), through a better decision making and giving more voice to water users in agricultural water governance. One of the most important activities is the analytical review of the current situation and existing institutions in both research and policy development and implementation in agricultural water. So the objective of the study was the establishment of the appropriate mechanisms for bridging research and policy in the case of water governance in agriculture. The research approach is based on interviews and face to face discussion. The main output of this activity is that organizations are working in silos with no or limited coordination between water and agriculture. Parallel structures in research and policy with no institutional pass ways, the weak governance has implications on sustainability of land and water, water use efficiency and water productivity, economic return for investments, that challenges food and water security set SDGs, despite the existing policies aiming at involving farmers and water users organizations in local decision making.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it