YOUTH UPRISING AND REVOLTS IN NIGERIA: AN EVALUATION OF THE #ENDSARS NATIONWIDE PROTESTS
Bibliographic record
Abstract
In civilized societies like the United States, Canada, Switzerland etc. civil unrests and protests are recognized channels through which citizens express their opinions and feelings about government policies and programmes. Available records show that the situation is different in Africa. This study, therefore, examined youth uprising and revolts in Nigeria: An evaluation of the #EndSARS nationwide protests. The paper argued that prolonged neglect and exclusion of the people (youths) from the governance process accounted for the distrust and disenchantment that sparked-off the nation-wide protests against the Nigerian state (government). Data for the study were curled from secondary sources while the analysis was based on the qualitative method. In terms of context, the study adopted the basic human needs theory as its theoretical framework in order to explain the reasons for youth uprisings and revolts in Nigeria. Findings from the study revealed that failure on the part of government at all levels to address the plight of citizens including the inhuman treatment meted out to youths by the police and other security agencies accounted for the youth’s mobilization and revolt across the country. However, political and economic reforms that will provide justice for all citizens especially aggrieved citizens and victims of state repression within the shortest possible time will help to restore trust and confidence between the government and the citizens (people).
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 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".