Processus multi-acteurs pour gerer l?utilisation des eaux usees en agriculture. In FrenchMulti-stakeholder processes for managing wastewater use in agriculture
Bibliographic record
Abstract
Wastewater use in agriculture is a complex phenomenon since it transcends typical sectoral and geographical policy and planning boundaries, and is influenced by opinions and perceptions. Planning for wastewater use typically requires the involvement of a number of government agencies covering health, water, sanitation, agriculture and irrigation, as well as researchers, community groups and the private sector. Where wastewater use is already taking place spontaneously and unofficially, how can these stakeholders come together to improve the management of the system to maximize the livelihoods benefits while minimizing impacts on health and the environment? One option is the formation of multi-stakeholder platforms, which provide a space for stakeholders to share opinions and seek negotiated solutions in an open and ?level? environment. How effective these are, what outcomes can be expected, and how they can be improved are all questions that are still being asked. This chapter presents three case studies in which multi-stakeholder processes were used to improve wastewater management for urban agriculture. Although differences were observed, there were several cross-cutting lessons. A critical factor is the starting point, including an agreed definition of the problem to be addressed, negotiated goals and a management structure that is acceptable to all stakeholders. When multi-stakeholder processes are externally initiated, as with those reviewed here, it is essential that project priorities are commensurate with local priorities. Finding an institutional home and anchor agency an improve long-term sustainability but care must be taken in considering how this impacts on existing power structures. Participation and representation greatly influence the effectiveness of the process and much may need to be done to support this, for example by strengthening local community groups. A factor that appears to significantly improve participation and engagement is having tangible outputs, which demonstrate to stakeholders the potential of multi-stakeholder platforms.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".