Bibliographic record
Abstract
New terrorism has been recently considered a new type of terrorism. The terrorism characteristics that have instigated the introduction of the term stem from the modern evolutions in most aspects of terrorism, such as its organizational structure, financing, recruitment, training, motivations, tactics, reach, targets, and lethality. This chapter reviews discussions surrounding new terrorism, explains its key characteristics and features, and demonstrates the dual role of the media and information technologies. Distinctions from conventional terrorism recognize it as loose, decentralized cell-based networks, using high-intensity weapons, religiously and vaguely motivated, using asymmetrical methods for maximum casualties, and highly skillful in using new media and information technologies. Moreover, the most critical features focus on how the functioning of new terrorism adapts new media technologies, which in turn, contribute to all of its aspects. However, it is concluded that regardless of the label—new or old—attention should be focused on the act and the actors, whether the ways they function utilize the conventional or adapt with the most recent technologies, media, and weapons, and most crucially, recognizing how fast and efficient terrorists are in utilizing the most advanced media and information technologies.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".