The Lived Experiences of Migrant Youths at Musina Town in the Limpopo Province of South Africa
Bibliographic record
Abstract
This study sought to explore and describe the lived experiences of migrant youths in South Africa by using Musina as a case study. Several studies reveal that Southern Africa is faced with an increased number of international population movements. Upon their arrival in the host countries, immigrants encounter a vast number of challenges. The new economic theory of migration was used to pursue the aim of this study. This study was qualitative wherein case study and phenomenological designs were triangulated to purposively select 18 migrant youths in Musina. Data was collected through semi-structured interviews and was analysed thematically with the assistance of Nvivo software. Findings reveal that most migrant youths due to problems around documentation are being hated by local citizens and exploited by employers that they end up performing impractical jobs without any benefits and job security. Stigmatisation was also found to be a challenge that migrant youths deal with in South Africa. There should be stringent security at the Beit-Bridge border post to mitigate illegal cross-bordering to South Africa. Integrative programmes should be developed to accommodate legal immigrants into the welfare of South Africa. Immigration laws should have a clause on the monitoring of any job done by immigrants in the host countries. Further research is also recommended in other provinces of South Africa and with significant others such as local citizens and government officials.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".