Water Scarcity in Communities, Coping Strategies and Mitigation Measures: The Case of Bulawayo
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
This paper looks at the impact of water scarcity in communities. This paper also evaluates various mitigation measures being employed by residents themselves, local authorities, non-governmental organization (NGOs) and the government. Bulawayo, Zimbabwe’s second largest city was chosen as a case study because the geographical and climatic conditions are such that it receives low and unreliable rainfall. The city has been facing water scarcity for close to a decade now. The water shortages have been recurring over and over again and this has resulted in the Bulawayo City Council introducing water shedding. This has resulted in residents being affected in many ways. Residents’ health has been compromised, sanitation levels have declined and education conditions negatively impacted. The research used purposive sampling. Key informants were interviewed from the City Council, Health department, residents association and NGOs. The research covered three suburbs that are Nketa 7, Entumbane and Newton West. The research found out that the high density suburbs were the most affected by water scarcity and NGO activities were also biased to these areas. Coordinated work between the government, local authority, NGOs and the residents has ensured that a major health crisis be averted.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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