Uplifting the Socioeconomic Life of Rural People through the Provision of Credit facilities and Entrepreneurship Development: The Role of CUSO International
Bibliographic record
Abstract
The study examines the correlation between Canadian University Student OverseaInternational credit facilities, entrepreneurship development programme and the socio-economic life of rural people in Southern Senatorial District. Adopting the survey research method, data was collected from 400 participants from a population of 3847 beneficiaries of the various CUSO programs in Southern Cross River State, using a structured questionnaire. The participants were selected using proportional stratified and accidental sampling technique. Elicited data was analyzed using descriptive statistics before the result was then subjected to correlation analysis at 0.05 confidence level. The descriptive analysis revealed that all the participants, 371 (100.00%), were beneficiaries. 335 (90.30%) participants reported that their socioeconomic status has improved since they benefitted from the CUSO microcredit scheme. 352 (94.88) participants reported that they were beneficiaries of the CUSO entrepreneurship program. 346 (93.3%) reported that the entrepreneurship development program has helped improved their employment status. From the parametric statistics carried out, it was discovered that there was a statistically significant correlation (r (369) = 0.113; p <0.05) between CUSO credit facilitiesand the Socioeconomic life of rural people. The result also revealed a statistically significant relationship between CUSO international entrepreneurship development programme and the Socioeconomic life of rural people. The study thereby calls for an expansion in the number of beneficiaries of the CUSO program.
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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 | 0.001 |
| 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 | 0.001 |
| 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".