‘Trying to Make South Africa My Home’: Integration into the Host Society and the Well-being of Refugee Families
Bibliographic record
Abstract
During the past two decades South Africa has increasingly become a host society for many forcibly displaced families from across the sub-Saharan region. This article draws on some of the findings of a qualitative study with the aim to investigate the impact of forced migration on the daily lives of refugee women and their families as well as their experiences in trying to integrate into the host society. The research population constitutes refugees from the conflict ridden countries of Burundi, the Democratic Republic of the Congo and Zimbabwe who reside in the inner-city areas of Tshwane and Johannesburg. Ager and Strang’s (2008) conceptual framework, which uses indicators of integration experiences, proved useful as an analytical lens. In discussing the findings specific reference is made to (a) markers and means of integration, (b) processes of social connection, and (c) facilitators of integration. The data revealed that Zimbabwean respondents and their families were slightly better off than the Congolese and Burundian participants in terms of social connection and means to achieve integration into the South African host society.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".