An Exploration of Transportation Terrorist Stabbing Attacks
Bibliographic record
Abstract
In his August 22, 2018 message to supporters of the Islamic State of Iraq and [greater] Syria (ISIS), Abu Bakr al-Baghdadi implored ISIS fighters in Syria and Iraq as well as those on various jihadist fronts in Africa, the Middle East, and Asia not to be dismayed by military setbacks suffered by the Islamic State, but to continue fighting, confident that Allah would ultimately reward those who remained steadfast with victory. In the same message, he exhorted homegrown jihadists abroad— “the fierce lions in the lands of the Cross—Canada, Europe, and elsewhere” to carry out simple attacks within their limited capabilities that would nonetheless have great psychological impact because they would strike in the enemy’s homeland.Previous reports by the Mineta Transportation Institute have addressed bombings (see "Suicide Bombings Against Trains and Buses Are Lethal but Few in Number" and "Explosives and Incendiaries Used in Terrorist Attacks on Public Surface Transportation: A Preliminary Empirical Analysis"). Car ramming attacks or what are sometimes called vehicular rammings have been the subject of more recent reporting. This report looks first at terrorist stabbing attacks against the public as a general phenomenon, and then examines stabbing attacks in public surface transportation venues.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".