Rural Livelihood Improvement: An Assessment of Households’ Strategies and Activities in Adamawa State, Nigeria
Bibliographic record
Abstract
The livelihood of rural residents is paramount in the development of the Nigerian state. The broad objective of this study was to assess rural livelihoods in Adamawa State, Nigeria. In specific terms, the study described rural residents’ socio-economic characteristics, identified their livelihood strategies and activities, examined factors affecting the undertaking of diverse livelihood activities, and also identified livelihood constraints in the study area. A sample of 480 respondents was selected from nine Local Government Areas of the State for the study. A semi-structured questionnaire was used in collecting data from 16 sampled villages. Descriptive statistics and Ordinary Least Square (OLS) multiple regression analysis were used in the data analysis. Findings of the study revealed that 86.7% of the respondents were male with a mean age of 46 years, and are mostly (74%) educated. Married persons constituted the majority (91.7%) having an average household size of the respondents was 7 persons. The main livelihood strategies in the area were; diversification, intensification, and migration. The respondents’ most common livelihood activities were agriculture-related. The study also revealed that the livelihood activities in the area are being significantly affected by age (X1), gender(X2), marital status (X3), household size (X4), educational level (X5), farm size (X6), remittance (X7), social group membership (X8), and access to credit (X9). The respondents’ foremost livelihood constraints identified in the study were; lack of basic social amenities (95.6%), poor political representation (92.9%), insecurity challenges (74.4%), lack of capital/financial exclusion (61.7%), and adverse climatic conditions (51.7%). Key among the recommendations of the study was the need for substantial investments in the provision of physical infrastructure in rural areas and also the provision of adequate security of lives and properties in conflict-affected areas.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".