The role of other economically active household members in poverty alleviation
Bibliographic record
Abstract
This paper extends the analysis on microfinance and poverty from the household perspective by focusing on the role of other economically active household members in alleviating household poverty. Results show that additional other economically active household members expand the pool of income earners in the households and this points to the significance of mobilizing additional household labor in the reduction of dependence on a single source of income in the household. Specifically, results from the earnings regression analysis and logit analysis indicate congruence with generally accepted theory on poverty, that is, the number of other economically active household members, their education, age (as proxy to experience) and employment status contribute to the income generation of a household and therefore, have a positive effect in reducing the probability of a household being poor. This implies that a household is more likely to be nonpoor if it has a greater number of other economically active household members because the effects of these explanatory variables to the households total income are interpreted as having the opposite effects on poverty.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".