Incidence of Multidimensional Poverty Among Riverine Households in Southwestern Nigeria
Bibliographic record
Abstract
What constitutes poverty transcends the lack of income but generally captures such other subjective and supplementary aspects that represent human functioning and capability. This view enables the design and implementation of policies to alleviate poverty among the poor, especially the riverine households with their attendant risks. Data were obtained from 448 riverine households in South-western Nigeria to examine the level of multidimensional deprivation and poverty among them. The mean household size was 5; fifty-six (56%) having less than minimum 9 year compulsory and basic education; only about 16% of them having members gainfully engaged and about 68% of the household heads engaging in Onshore livelihood activities. Majority (60.3%) of the households suffered deprivation in eight indicators (61.54% of the total possible number of deprivation) and above, all (100%) of the riverine households being adjudged poor in about 6%, 12% and 19% respectively’ of the thirteen dimensions of deprivation. At dual cutoff value (k = 8), the adjusted multidimensional poverty rate of the households (M0 = 0.3422); adjusted poverty gap (M1 = 0.1608), and poverty severity (M2 = 0.0761) showed high level of inequality among the deprived households. Conclusively, poverty was manifested in basic standard of living commodities and services among the riverine households as indicated by their low level of education, limited access to hygienic source of drinking water, food, energy, health care, toilet facilities as well as improved means of livelihood.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".