Bibliographic record
Abstract
Ways of knowing against colonialism In the 1990s, the North American Free Trade Agreement (NAFTA), the Violence Against Women Act (VAWA), and US and Canadian boarding/residential schools’ practices led to an increase in cases of missing and murdered Indigenous women from the US-Mexico border, Guatemala, Canada, and the United States. Indigenous artists aiming to recontextualize these state-sponsored instances of violence created works grappling with time, ancestry, and relationality. Lilian Mengesha interprets the works of these artists within a decolonial context through an aesthetic frame she calls “critical dreaming.” Using methods from performance studies, gender studies, and Indigenous studies, Critical Dreaming considers artists as expert world makers. Mengesha examines selected works by Lara Kramer, Regina José Galindo, Rebecca Belmore, Monique Mojica, LeAnne Howe, and Sky Hopinka, demonstrating how each materializes alternative modes of experiencing time, making kin, and communing with land. Mengesha argues that critical dreaming is a performance that advances material and embodied practices of survival, both individual and collective, to challenge colonial and nationalist discourses invested in a teleology of disappeared people, history, and land. Her writing provides valuable insight into the intergenerational effects of settler colonialism on Indigenous communities throughout the Americas, looking at how artists build worlds anew through Indigenous ways of knowing and making inspired from the past and repurposed for the present. Critical Dreaming offers a resonant framework for understanding Indigenous embodied ways of knowing that work against colonial attempts to discredit or disappear forms of imagination, relationality, and resistance connecting disparate Indigenous communities. This powerful book urges readers to recognize how Indigenous artists contribute to ongoing struggles against multiple forms of colonialism.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.023 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".