Bibliographic record
Abstract
This paper examines the distribution of welfare in Uganda in 1997. The data used was obtained from a household survey conducted by the Economic Policy Research Centre (EPRC) in the first quarter of 1997. The analysis of the data focused on the distribution of welfare as measured by household consumption expenditures. It also focused on the attributes of the poor and the very poor households and on the characteristics of their component members. The major findings of the analysis are that the poor are predominantly found in the rural areas, are less educated, have large household sizes, and are primarily agricultural workers. They lack basic services and amenities and have very low levels of expenditure. Inequality levels are high in Uganda as shown by the summary Measures of Inequality. Across regions we also see some divergence in welfare distribution and it is conclusively clear that welfare is unequally distributed in Uganda. The poor are sharing very little of the benefits of growth, while the rich are enjoying the greatest share of the benefits. Eastern Africa Social Science Research Review (EASSRR) VOLUME XVI No. 2 June 2000, pp. 71-94
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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 | 0.013 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".