Reducing Unemployment, Poverty and Promoting Empowerment through Skills Acquisition (TVET): A Case Study of Returnee Migrants
Bibliographic record
Abstract
This paper explains recent statistics and phenomena related to returnee migrants in Edo state, Nigeria. The significance of this paper is that it creates awareness on causes and motives behind irregular migration leading to repatriation (returned migrants). Based on data gathered from most research participants (returnee migrant) – the quest to improve one’s socioeconomic living conditions are the motives behind most Nigerians’ migration journey (regular or irregular) to western countries (i.e., Europe, Canada, USA, etc.). The socioeconomic imbalance in Nigeria is mainly caused by the high rate of unemployment and poverty; thus, the majority of Nigerians are of the opinion that migrating to western countries, is a potential pathway to an improved socioeconomic living condition. This paper further suggests – skill acquisition (TVET) as an approach to reduce unemployment and poverty; thus, economically improving the socioeconomic living conditions of the majority of Nigerians.
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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 | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".