The Importance of Legislation in Dealing with Extremism and Terrorism: The Experience of Trinidad and Tobago
Bibliographic record
Abstract
While there are vast disparities in size and population between Canada and Trinidad and Tobago (T&T), there are important commonalities between the two including, ethnic and religious diversity, and adherence to strong democratic principals. T&T’s Muslim community represents approximately 5% of the population and has been a strong fiber in the social fabric since 1845. The actions of a small number of citizens has however led to T&T being labelled as having the highest foreign terrorist fighters (FTFs) per capita in the western world. Trinidadians have also been the victims of international terrorism including 9/11 and the Westgate Shopping Mall attack in Kenya. These issues together with the evolving tactics of terror organizations such as ISIL, coupled with T&T being a target rich environment, places terrorism high on the national security agenda.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.014 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".