Would halving unemployment contribute to improved household food security for men and women?
Bibliographic record
Abstract
abstract South Africa faces great challenges with extremely high unemployment and deep poverty. A large proportion of households are challenged to meet minimum required nutrition levels. In 2009, the HSRC prepared employment scenarios to see how unemployment might be reduced by 50% between 2004 and 2014, even in the context of the downturn. These scenarios consider what working people might earn in these different scenarios. There is a question as to whether wage income, even in a context of substantially reduced unemployment, would be sufficient to enable working households to achieve nutrition security by 2014. There are substantial differences in households led by men and women. Women have a more precarious foothold in the labour market, tending to be located in lower-paid sectors. The downturn has especially exacerbated this disadvantage, as proportionately more women became unemployed. The economic upturn has led to jobs being created for men, but continued job losses for women. This briefing conside...
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".