Bibliographic record
Abstract
The academic and institutional battlefield is littered with the best intentions of those attempting to bring a universally recognized definition to the term ‘terrorism’. The concept of ‘where you sit is where you stand’ certainly applies to such endeavors. In addition to considering how best to integrate such fundamental questions as who, what, where, why and how in a definition of the term, attempts have been confounded and complicated by where definitional efforts have been centered within a particular community. Do you adopt a social science or quasi-scientific approach? From a jurisprudence and law enforcement perspective? Terrorist financing? Intent and motivation? Psychological drivers and personal profiles of individual terrorists? Organizational structures? Cultural and anthropological approaches? Rationality and mental health? Historical considerations? Critical study interpretations? All this has made for terrorism being a contested concept over the decades. As observed by Schmid and Jongman, and as we shall explore, “The nature of terrorism is not inherent in the violent act itself. One and the same act can be terrorist or not, depending on the intention and circumstances.” But how terrorism is defined by whatever community is not a trivial issue. Definitions carry political and policy consequences that govern the counterterrorism space and how threats and risks are articulated going forward. How the threat environment endures is often just as much an outcome of how a state elects to respond to the threat, as it is the agenda of terrorist entities. And terrorism charges cannot be prosecuted if there is not at least some notion of how motivations, intentions and acts are defined in statutes. Received: 01-05-2024 Revised: 01-14-2024
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.029 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".