Effects of capacity building on rural women involvement in Climate Smart Agriculture initiatives in Rivers state, Nigeria
Bibliographic record
Abstract
Abstract The study assessed the effects of capacity building on rural women involvement in Climate Smart Agriculture (CSA)initiative in Rivers State, Nigeria. Respondents were leaders of rural women cooperative societies in Rivers State who were randomly selected from 23 Local Government Areas in the State. Structured questionnaire administration and Key Informant Interview was used to collect data while frequency counts, mean and percentages were employed to analyze the data collected. Results showed that the rural women interviewed were mostly adults, as majority (71.8%) were within the age range of 40 - 59 years. Majority (62.52%) were engaged in business/trading and other non-agricultural income generating activities, such as civil service (21.89%), income from pensions (3.13%), while 12.5% of the respondents had no other income generating activity aside farming. Some (40.63%) of the rural women had Senior Secondary Certificate as the highest form of education. Only 43.75% were aware of CSA, with 62.51% of them indicating low level of CSA knowledge. The major CSA management practices they know include mixed farming (50.0%), crop management practices (40.63%), application of indigenous knowledge and practices (25.0%) and soil management practices (25.0%). Approximately 84% have not attended CSA training before now. All the rural women (100%) used for the study upheld that CSA training is helpful in improving their CSA knowledge, imparted their readiness to adopt CSA practices (94%) and equipped them to be more involved in CSA initiative (100%). The major effects of capacity building on rural women involvement in CSA initiative are better knowledge of CSA for increased use of CSA practices (X̄ = 3.72), capacity to add value to their farm products (X̄= 3.69) and capacity to train others on CSA practices (X̄= 3.50). Regular training on CSA components by both government and private agencies could help in strengthening and sustaining rural women active participation in CSA initiative in the state and beyond.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".