Competency Improvement needs of Women in Agriculture in Processing Cocoyam into Flour and Chips for Food Security in South Eastern Nigeria
Bibliographic record
Abstract
This study focused on the identification of competency improvement needs of women in agriculture (WIA) in processing cocoyam into flour and chips. To achieve these objectives, four research questions guided the study. Descriptive survey research design was adopted for this study. The study was conducted in South-eastern Nigeria made up of Abia, Anambra, Ebonyi, Enugu and Imo State The target population for this study was 362 women processors. It was found out that women processors required improvement in cocoyam processing enterprise as follows: planning competencies (12 competency items), processing cocoyam into flour (13 competency items), processing cocoyam into chips (13 competency items) and marketing (7 competency items). It was therefore recommended that co-operatives, government agencies, and relevant NGOs should help use the findings of this study to improve acquisition of competencies of women in cocoyam processing for food security in South-Eastern 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 | 0.003 |
| 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 | 0.001 |
| 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".