Food poverty assessment in Ghana: A closer look at the spatial and temporal dimensions of poverty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The multifaceted nature of poverty in terms of its duration or chronicity, systematic changes, seasonality, variation, and risk or vulnerability makes its measurement and analysis complicated, especially in lower-income countries. In Ghana, data show that absolute poverty remains prevalent, and inequality has been rising. Despite the gradual decline in poverty, spatial income inequality has also become a concern in Ghana. This study develops a Foster-Greer-Thorbecke Poverty Measure based spatiotemporal model to investigate the variation in food poverty in Ghana. Application to population-based surveys fielded in 2012/13 and 2016/17 indicate that considerations of temporal and spatial dimensions of poverty have implications for gaging the level of deprivation among households and the potential allocation of scarce resources via policy to achieve poverty alleviation objectives. A model that jointly considers both the spatial and intra-annual dynamics arguably considered the most accurate and flexible but data-intensive one, resulted in the mean unconditional food poverty rate of 50%, with the lowest rate being the Northern Region in March (45%) and the highest rate being in the Upper West Region in June (54%). Overall, cost-wise, this flexible model also results in the highest potential cost savings.
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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 | 0.003 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it