Exploring BRICS contribution in addressing youth unemployment in South Africa.
Bibliographic record
Abstract
Youth unemployment is a global issue and is significantly worse in developing countries.South Africa has one of the world's highest youth unemployment rates, with almost half of its youth population (between the ages of 15 and 34) unemployed (52,18%), as recorded in the final quarter of 2019.This study explores BRICS contribution in addressing youth unemployment in South Africa.Made up of Brazil, Russia, India, China and South Africa, BRICS is a coalition of emerging economies that support the economic growth and development of its members.Liberal institutionalism theory is used in this study to understand the relevance and contribution of coalitions like BRICS in increasing aid and cooperation among member states to address various socioeconomic challenges.Classical growth theory is used to understand and unpack the economic aspects of youth unemployment.This study employs a qualitative research method and data is collected from books, articles, scholarly journals, and official reports such as South Africa's Quarterly Labour Surveys, BRICS Labour and Employment Minister Declarations, BRICS Summit Declarations 2015-2019, and Trade reports from the Department of Trade, Industry and Cooperation.The data gathered from the existing literature was analysed using the content analysis method.The findings show a strong correlation between youth unemployment, the South African education system and lack of skills development.The study explores multilateralism as it places an important role in economic growth and development through increased trade and partnerships which allow member states to pursue common interests.The study also examines the various contributions BRICS has made in addressing youth unemployment in South Africa.The findings show that BRICS countries have dedicated programmes to addressing youth unemployment within member states, specifically by addressing its underlying issues.The study concludes that through BRICS initiatives, South Africa has benefited through investments in education, intra-BRICS exchange programs, job creation, foreign investment, and increased trade relations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".