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YOUTH UPRISING AND REVOLTS IN NIGERIA: AN EVALUATION OF THE #ENDSARS NATIONWIDE PROTESTS

2022· article· en· W4281992098 on OpenAlexaboutno aff
Johnson Alalibo

Bibliographic record

VenueInternational Journal of Scientific Research in Humanities Legal Studies and International Relations · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
Fundersnot available
KeywordsDistrustGovernment (linguistics)Context (archaeology)Political sciencePoliticsState (computer science)Economic JusticeNeglectDisenchantmentPublic administrationLawPsychology

Abstract

fetched live from OpenAlex

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).

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.308
GPT teacher head0.483
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueInternational Journal of Scientific Research in Humanities Legal Studies and International RelationsSame topicTerrorism, Counterterrorism, and Political ViolenceFrench-language works237,207