Perceptional Evaluation of the Impact of Second National Fadama Project on Gender Income, Output and Decision-Making Power in Abuja, Nigeria
Bibliographic record
Abstract
The study perceptionally evaluated the impact of the Second National Fadama Development Project (Fadama 11) on the income, output and decision-making power of the male and female farmers who participated in the project. Simple random technique was adopted for sample selection while questionnaire was used for data collection. A sample of 284 (159 males and 125 female) farmers were randomly selected in 8 locations or Fadama Development Areas (FDAs) in Abuja. The data were analysed with two-way independent factorial analysis of variance. Results indicated that there was no significant difference (p > 0.05) in the impact of the project on the income, output and decision-making power of the male and female farmers who participated in the project. The mean responses for the male farmers on income, output and decision-making power were 3.37, 3.20 and 3.30 respectively while those of the female farmers were 3.35, 3.08 and 3.35 respectively. On the contrary, there were locational differences (p < 0.01) in the impact of the project on the income, output and decision-making power of the farmers. The mean response showed that farmers in Bwari and Karshi areas perceived the impact of the project on the three indicators more than farmers in other locations. Although, the interaction effect of gender and location was not significant (p > 0.05), the mean responses indicated that in some locations, the project impacted more on the male farmers’ income, output and decision-making power while in some locations, the reverse was the case in favour of the female farmers. Based on the grand mean responses for income (3.36), output (3.13) and decision-making power (3.36), the paper concluded that the project had a moderate impact on gender in the study area.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".