The impact of informal settlement expansion on greywater generation: a potential missed opportunity?
Bibliographic record
Abstract
ABSTRACT South Africa is a semi-arid country with drought on the rise. The government reports that over 3,400 informal settlements exist nationally that both require potable water and generate greywater that could be treated and reused. The current study investigated this using the Zandspruit informal settlement in the Gauteng province of South Africa. Aerial photography graphic information system (GIS) layers of Zandspruit were traced in approximately 3-year intervals between 2000 and 2023, and drone photography was employed in 2022. Using survey data collected within the settlement, in almost a quarter of a century, the usage of potable water and generation of greywater have increased by over 730% to 575 and 400 m3 per day, respectively. More than 62% (248 m3) of greywater was reported as discarded daily outside around dwellings, foregoing any reuse potential. It is important to study how this wasted resource could be purified and reused to contribute to the water needs of the country, and to mitigate health risks and environmental pollution concerns within the community due to greywater exposure.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".