Bibliographic record
Abstract
On September 19th 2019, the Canadian Association for Security and Intelligence Studies (CASIS) Vancouver hosted its roundtable meeting which covered “The Nature of Contemporary Terrorism.” The following presentation featured Dr. Robert Farkasch, a faculty lecturer in the Political Science Department at the University of British Columbia. Dr. Farkasch offers instruction in international political economy, international relations and terrorism studies. In his presentation, Dr. Farkasch appears to argue that religiously defined terrorism is the most dangerous ideological variant of terrorism and that the cause of terrorism is entrenched in our fear of death. The subsequent roundtable discussion centred around a case study of Brenton Tarrant, a 28-year- old Australian man that opened fire upon two Mosques in Christchurch New Zealand earlier this year, killing 51 people. Many called the attacks Islamophobic due to his targets and the content within a 74-page manifesto that Tarrant authored and released beforehand. Audience members at the roundtable discussed the nature of Tarrant’s attacks and how social media platforms could address radical positions within online spaces.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".