Globalization and Terrorism in Nigeria: A Retrospective Reflection
Bibliographic record
Abstract
Nigerian sovereignty for more than a decade was challenged by the onslaught of Sunni Jihadism in the North-East. The Jihadist insurgency took a more frightening dimension with the emergence of Islamic State of West Africa Province, ISWAP in alliance with Jama’atu Ahlis Sunna Lidda Awati Wal-Jihad, otherwise known as Boko Haram in bid to Islamize a secular nation-state. This paper in retrospective sense examined the frightening reality and, argued that this absurdity is facilitated by global spread of Islamic extremism and terrorism. The discourse adopted qualitative research design to explore the relevance of secondary and non-participant observational sources of data collection and content-analyzed issues and enfolding events. The discourse revealed that well-coordinated suicide bombings of Louis Edet House, Nigeria Police Headquarters on June 16, 2011 and United Nations building on August 26, 2011 at Abuja, the Federal Capital, were visible manifestations of global terrorist links of Boko Haram with Al-Qaeda. And, subsequent pledge of allegiance to ISIL in March 2015 watershed the varicosity of global terrorism in Africa most populous country. In credence to these findings, the discourse suggested holistic review of national security strategy and operational
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".