Understanding the Population of People Experiencing Homelessness in Cape Town and their Service Use
Bibliographic record
Abstract
Cape Town, South Africa, has an estimated 14,357 people living on the street or in temporary shelters. Current responses to homelessness are either punitive—focusing on law enforcement and displacement—or compassionate, offering basic relief like food or handouts. Neither approach is effectively addressing the root causes of homelessness, and the number of homeless individuals continues to rise. This paper advocates for a developmental approach that provides structured support to help people exit homelessness. There is limited knowledge about the causes of homelessness in South Africa, the services utilized by those affected, and the kind of support needed for sustainable solutions. To address this gap, a survey of 350 homeless individuals in Cape Town was conducted, gathering data on demographics, service use, income sources, health, substance use, and interactions with legal systems. The results reveal that the average duration of homelessness is 8.6 years, with over 70% of respondents experiencing homelessness for more than a year. The main causes of homelessness were identified as structural issues such as lack of income, housing access, and loss of family support. Only 11% of participants were in temporary shelters, and their average daily income was around R78 (about $4 USD). Substance use disorders were prevalent, affecting 63% of respondents, while 54% reported being arrested at least once during their experiencing homelessness. Most had not accessed developmental services, highlighting a critical gap in support. If the current approach persists, homelessness will worsen, with more individuals becoming entrenched in chronic homelessness. A shift towards a developmental approach is urgently needed, focusing on personalized support, affordable housing, rehabilitation, psychosocial services, and employment programs to facilitate a meaningful exit from homelessness.
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How this classification was reachedexpand
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) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".