Child Poverty and Gender and Location Disparities in Zimbabwe: A Multidimensional Deprivation Approach
Bibliographic record
Abstract
Despite global progress in the last 20 years in measuring multidimensional child poverty, most studies have focused on all children generally. This approach distorts how poverty affects differently aged and situated children. By measuring multidimensional child poverty among children ages five years and below in Zimbabwe ( N = 6,418) and analyzing how this problem is correlated with gender and location, respectively, this article attempts to address such knowledge gaps. Using a rights‐based deprivation approach, 14 deprivation variables are selected from Zimbabwe’s 2015 Demographic and Health Survey secondary data. The items are tested for validity, reliability, and additivity, and deprivation estimates are established for those which are valid, reliable, and additive. Thereafter, their correlations with gender and location, separately, are computed. Analysis demonstrates that the most common deprivation forms among the children are early childhood development (78 percent), water (46 percent), health care (44 percent), sanitation (40 percent), shelter (30 percent), and nutrition (13 percent), separately. While there are quite negligible share differences between deprived boys and girls, all deprivations are highest in rural areas. Although all deprivations have largely insignificant correlations with gender, most are significantly correlated with location. Ultimately, the article highlights key disparity areas for effective antichild poverty interventions and future child poverty research.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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; 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".