From Turtle Island to Palestine: settler-colonial Canada, genocide, and Indigenous foreign policy
Bibliographic record
Abstract
In this article, we question how Canada, so adamantly in favour of human rights and a rules-based order, can shield Israel from accountability for war crimes, crimes against humanity, and genocide. We give examples of everyday Canadian institutions built on the genocide of First Nations and invested in genocide through contemporary weapons companies and related industries. We quickly move, however, to understanding popular sentiment regarding genocide and how that has manifested in protests, encampments, and solidarity statements and actions. We identify how, over centuries, Indigenous nations have been and continue to be at the forefront of international diplomacy, unity, and visionary forms of protection of all peoples, lands, waters, plants, and wildlife. We contrast this with misinformed and ill-informed policy efforts that sustain settler colonialism in Turtle Island and Southwest Asia, including Palestine. We conclude the article with some thoughts on how the same path to freedom and justice lies ahead in both Turtle Island and Palestine, and how efforts to forge this path take place in active solidarity among Indigenous nations, including Palestine.
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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 | 0.003 |
| Science and technology studies | 0.023 | 0.015 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".