World of statues: the “war on terror,” memorialisation, and colonial violence
Bibliographic record
Abstract
As the “war on terror” expands to new frontiers, we reflect on how it is memorialised through statues and monuments that serve to erase the imperialist and racialised violence it has embodied (and continues to embody). We write this essay as the government of Canada is developing plans to build a new memorial in its capital city, Ottawa, to commemorate its protracted and costly participation – as “empire’s ally” – in a U.S.-led militaristic campaign in Afghanistan in the name of combatting “terrorism” (Albo and Klassen 2012; Brewster 2021). Canada withdrew its troops from Afghanistan a decade ago and the U.S. government plans to withdraw its troops by September 2021 (Ryan and DeYoung 2021). While the Americans have been forced from Afghanistan mere weeks before the withdrawal that was to mark an end to the 20-year military campaign against terrorism and, with what appears to be a long period of instability ahead, the current moment can be considered within the ongoing mutation of the “war on terror” from a war (in Muslim countries) overseas to a war (against “dangerous” Muslims) everywhere.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".