Bibliographic record
Abstract
A decade after the bombing of Air India Flight 182 in June 1985, many Canadians were shocked to learn that the Babbar Khalsa Society – a militant organization dedicated to the establishment of an independent state in northern India, members of which are believed to have planned the Air India bombing – had been granted charitable status in Canada. Although the organization's charitable status was revoked in 1996, reports also suggested that funds collected to support Sikh temples in Canada may have been diverted to support Sikh militancy in India. This article examines the relationship between charities and terrorist financing in Canada, reviewing Canada's legal framework in order to evaluate its adequacy to limit the use or misuse of charitable organizations for terrorist financing. This evaluation is based on two important considerations. First, as experience with the Babbar Khalsa Society and Sikh temple funds sadly demonstrates, effective supervision and regulation of charitable organizations is essential to prevent their being manipulated by individuals and groups who seek to exploit the legitimacy and fiscal benefits that these organizations enjoy in order to finance terrorism. Second, as many charities are small organizations with unpaid volunteers and very few have any connection with terrorist activities, charities should generally be viewed as allies in the struggle against terrorism rather than suspects. As a result, government supervision and regulation of the charitable sector should be proportionate and risk-based – emphasizing capacity building and best practices to prevent the use or misuse of charitable organizations for terrorist financing, ensuring transparency and self-regulation to the greatest extent possible, scrutinizing transactions and organizations that pose the greatest risks for terrorist links, and limiting more serious regulatory sanctions to the rare instances where charities provide support to terrorist organizations.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".