Bibliographic record
Abstract
People all over the globe have become very familiar with the term terrorism due to its common and worldwide occurrence. Terrorism has been committed by states, governments, organizations, groups, and individuals throughout its long history. Despite the large number of definitions by governments, global institutions, academics, politicians, security experts, and journalists, there has been no single universally agreed-upon definition of terrorism so far for a variety of reasons. This chapter critically analyzes discussions and definitions of terrorism in an attempt to contribute to a fair and balanced understanding of terrorism. It discusses how subjectivity has been an obstacle in understanding terrorism due to the pejorative nature of the term. Debates around the highly contentious concept of terrorism in terms of its distinctive nature, motivations, goals, and means in comparison to other forms of violence are discussed, and several definitions of terrorism are analyzed. It is evident that obtaining public attention is the ultimate aim of terrorism in relation to communicating specific messages and both the use of and by the media. While definitions of terrorism struggle to demonstrate exhaustive lists of descriptions, traits, components, conditions, and elements of terrorism, disagreements on these definitional items and features create ambiguities in understanding terrorism. The chapter, then, concludes with discussions on eliminating controversial and subjective definitional items and features to introduce a definition that can help provide an objective understanding of terrorism.
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 | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| 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".