Bassmati Community: Innovating WASH and Climate Solutions in Jordan
Bibliographic record
Abstract
This paper presents a descriptive case study focused on developing a local model with global applicability for fostering innovative entrepreneurial and applied scientific research projects in the climate, water, sanitation, and hygiene (WASH) sectors.Our study examined the effectiveness of UNICEF's water, sanitation, and hygiene programs in mitigating disasterrelated effects on human and environmental health at the Bassmati Innovation Community in Jordan.This study reveals significant advances in disaster mitigation strategies, including improved sanitation facilities, innovative water management strategies, and improved community engagement.These results provide a practical framework for similar initiatives in the future in addition to highlighting the crucial role that the Bassmati Community plays in the development of Jordan's water, sanitation, and climate response sectors.The study's innovative model, demonstrated through the achievements of the UNICEF Innovation Hub, provides a scalable and adaptable approach for universities and centers focusing on climate and waterrelated projects.As a result of this model, the Arab region and global communities will benefit from its addressing of pressing environmental challenges beyond local boundaries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".