Widowhood and multidimensional poverty: Evidence from Nigeria
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
Abstract Poverty among widows has received little empirical attention in Africa despite women's severe vulnerability to death shock. We provided empirical evidence on widow households' transition in and out of poverty and factors influencing their probability of being in poverty. The Markov transition probabilities show moderate but increasing positive transitions for severely poor widows. Non‐poor widows are stayers who primarily sustain their non‐poor class. The ordered logit estimation shows that higher dependency ratio increases the chances of a widow being severely poor. Being an older widow and having literacy skills reduced the probability that a widow household will be severely poor. Household size and dependency ratio are noted to play important roles in the probability of transitions across poverty classes as shown by the estimated multinomial logit model. These findings are robust to alternative poverty measure, estimation method and different set of weights. Generally, the results echo the need for social safety nets to cushion widows' financial strains. Life insurance policy for spouses, increased sensitization of widows of their rights and adult education programmes targeted at widows could mitigate the negative impact of widowhood on women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it