Weapons of Mass Destruction and Modern Terrorism: Implications for Global Security
Bibliographic record
Abstract
The hazard of biological, chemical and nuclear materials, regarded as Weapons of Mass Destruction (WMD), intercalating the arsenal of terrorists is the biggest crime and challenge against humanity. Every such crime and challenge ought to be named appropriately; and state actors experiencing such owe it to their citizens to act speedily and with certainty against terrorists. Even with the on-going war on terrorism, there has been a surge in terrorist activities in some parts of the world. Terrorists in our contemporary age have also embraced startling trends in their operational mode since the 11 September 2001 fanatic attacks in New York and Washington D. C. The devastating effect of these twin attacks has raised global concern about the potential use of WMD by Al-Qaeda, the Islamic State of Iran and Syria (ISIS), and their affiliate groups. One major issue of great concern in recent times, apart from the propensity of the terrorist organizations to acquire WMD, is the involvement of state actors that secretly acquire or claim to have acquired them for the purposes of electricity generation. Notably, too, is the trend in modern scientific and technological improvement which has increased the nature of, and access to, WMD. This research, therefore, attempts to access the implication and impact of WMD as terrorists put them to use. The study also examines the concept of terrorism and WMD. Also examined is the general implication of the use of WMD and the challenges this might pose to the international community, considering the current trends in their acquisition by some states and non-state actors. The investigation suggests appropriate counter-measures to thwart terrorists’ effort to acquire WMD. The study also adopted the qualitative approach of research to analyse the sophistication adopted by new terrorist groups particularly by the ISIS terrorist network; the al-Qaeda group and other splinter groups. Thus, historical research is most appropriate for this study, and secondary source of data was adopted as its methodology.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".