Tracking Financial Complicity in Israeli War Crimes and Genocide: Instances of Aiding and Abetting in the Canadian Charitable Sector
Bibliographic record
Abstract
Utilizing tax return data gathered through Access to Information requests, this article probes the Canadian charitable sector for evidence of financial complicity in the aiding and abetting of Israeli war criminality and genocide. The evidence suggests that of the overall charitable donations heading from Canada to Israel, a significant percentage is bankrolling Israeli intermediaries directly involved in illegal settlement and military-related activities, in contravention of Canadian and international legal frameworks. Troublingly, an exhaustive probe of the potential Canadian charitable sector complicity was not possible, due to substantial deficiencies in reporting requirements. The overall lack of regulatory enforcement surrounding donations heading to Israel—in the light of credible unresolved accusations of anti-Muslim bias levied against the Canadian charitable regulator, specifically as it pertains to over-enforcement—raises troubling questions surrounding complicity in Israeli war criminality/genocide.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".