Bibliographic record
Abstract
This article explores the representation of cultural genocide in the case of Canada’s Indigenous peoples in Joe Sacco’s documentary graphic narrative Paying the Land, which focuses on the Indigenous Dene peoples in the Canadian Northwest Territories. Specifically, the article discusses Sacco’s depiction of perpetrators of the so-called Indian Residential School System (IRSS), which is contrasted with portrayals of intracommunal violence and Indigenous perpetrators. Through graphic narrative means, Paying the Land presents the latter as an aftereffect of the former and extensively explores how cycles of domestic violence and substance abuse were initiated through the attempted destruction of Indigenous peoples as a group, a process in which the residential schools played an important role. In doing so, Sacco specifically addresses a North American audience as implicated subjects who, like himself, are entangled in settler-colonial histories. He investigates the complexities of perpetratorship and accountability that involves not only the policymakers and residential school staff but also North American society at large. In respect to intracommunal violence among the Dene, Paying the Land seeks to shift public perception from inherently ‘deficient’ Indigenous culprits toward an understanding of the colonial policies that have purposefully eroded social cohesion among Indigenous peoples.
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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 | 0.034 | 0.045 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".