Role of Sustainable Development Goals in Combating Youth Unemployment: A Case Study of the Federal Capital Territory (FCT) Abuja, Nigeria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Globally, inequality has persisted with especially the youths excluded from full participation in economic, political and social activities. Relatedly, youth unemployment has been known to undermine economies, threaten the peace and destabilize communities, if unchecked. This study investigates youth unemployment, using the Federal Capital Territory (FCT), Abuja, Nigeria, as a case study; with a randomly selected sample size of 1,000 unemployed persons, in the 18–49-year-old age group. It examines the causes of youth unemployment as well as levels of awareness of the UN’s SDG-4 (Quality Education) and SDG-8 (Decent Work) in the working-age population, and the roles of these SDGs and government in combatting unemployment. Frequency and average-mean descriptive statistics of the factors causing youth unemployment indicated low levels of education, lack of employable skills and experience, and poor policies, etc., as predominant causative factors. Regarding the SDGs, the results revealed a low level of awareness and attainment in the population sampled. Education is central to achieving the SDGs; which can, in turn, mitigate unemployment and impel decent work. The introduction of private sector-driven, government-initiated mandatory one-year skills acquisition and developmental schemes for the youths as well as the provision of soft loans for participants to facilitate entrepreneurial ventures are recommended to reduce youth unemployment and promote economic development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it