Challenges and Opportunities Experienced by Service Providers at Homeless Shelters in Tshwane, South Africa During the COVID-19 Pandemic
Bibliographic record
Abstract
While the coronavirus disease of 2019 (COVID-19) pandemic exerted a devastating impact on all members of society, it highlighted the worsening inequalities experienced by marginalised groups such as people experiencing poverty and homelessness in South Africa. The pandemic also exacerbated the multiple demands and stressors of service providers working in homeless shelters. Hence, the study examined the experiences of service providers in terms of challenges and opportunities derived from working at homeless shelters in Tshwane, South Africa, during the hard lockdown from 27 March to 30 April 2020. Guided by a qualitative approach, five service providers were interviewed online. Thematic analysis revealed organizational challenges, such as a lack of knowledge and preparedness regarding disaster management, while client challenges included getting service users to adapt to living with rules. Organizational opportunities included the opportunity for the organization to conduct research, while personal opportunities included the learning experience of working with a vulnerable population during an unprecedented pandemic. Findings highlight the need for programmes to support the wellness needs of service providers and the development of a national policy on homelessness.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".