Entrepreneurial Training Needs of Illiterate Women in Cross River State, Nigeria
Bibliographic record
Abstract
In order to improve on the curriculum and participation rate of adult learners in the current Adult Basic Education (ABE) program in Nigeria, this explorative study investigated the entrepreneurial (or vocational) training needs of illiterate women in Cross River State (CRS). Three research questions were posed to elicit from the participants their demographic characteristics, perception of the ABE program and perceived entrepreneurial training needs. The descriptive-survey design was adopted for the study. The focus group discussion along with probing interview sessions were held with a sample of 240 women learners drawn from the urban and rural ABE centers. Frequencies, percentages and bar charts were used to report the data. The study shows that majority of the women are young, single, unemployed and dropped out of school and perceived the current ABE as not meeting their needs. Majority of the subjects desire training in home management, clothing and textiles. Those in the rural areas prefer training in agricultural production. A few of those in the urban centers prefer training in computer/secretarial related skills. The major conclusion of the study is that the learners (women) should be involved in identifying their learning needs that would at the end of the program empower them to improve on their livelihoods.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".