A Functioning Approach to Well Being Analysis in Rural Nigeria
Bibliographic record
Abstract
The Nigerian rural population is described by low productivity, little formal education and poverty. The need for more studies on the issue of wellbeing of rural population is hinged on the continued development of approaches that give better understanding of the phenomenon. This paper attempted to use Amartya Sen’s capability approach to assess multidimensional well being in rural Nigeria in six functioning dimensions obtained from the Nigerian Core Welfare Indices Survey using the fuzzy set theory. A binary logistic regression was also carried out to isolate the factors that determine the attainment of a pre determined level of well being after computation with the fuzzy set analysis. The results showed that rural Nigeria is an agrarian society; the functioning with the highest level of achievement out of the six dimensions studied was Housing, while asset ownership/income was the least achieved dimension in rural Nigeria. Results further revealed that belonging to female headed households, increasing age and being employed in the private (formal) sector as well as having some form of post secondary education enhances well being while being employed within the agricultural sector significantly reduced the well being of rural households in Nigeria.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".