Raven, Dog, Human: Inhuman Colonialism and Unsettling Cosmologies
Bibliographic record
Abstract
Abstract As capitalism's unintended, and often unacknowledged, fallout, humans have developed sophisticated technologies to squirrel away our discards: waste is buried, burned, gasified, thrown into the ocean, and otherwise kept out-of-sight and out-of-mind. Some inhuman animals seek out and uncover our wastes. These ‘trash animals' choke on, eat, defecate, are contaminated with, play games with, have sex on, and otherwise live out their lives on and in our formal and informal dumpsites. In southern Canada's sanitary landfills, waste management typically adopts a ‘zero tolerance’ approach to trash animals. These culturally sanctioned (and publicly funded) facilities practice diverse methods of ‘vermin control.’ By contrast, within Inuit communities of the Eastern Canadian Arctic, ravens eat, play, and rest on open dumps by the thousands. In this article, we explore the ways in which western and Inuit cosmologies differentially inform particular relationships with the inhuman, and ‘trash animals' in particular. We argue that waste and wasting exist within a complex set of historically embedded and contemporaneously contested neo-colonial structures and processes. Canada's North, we argue, is a site where differing cosmologies variously collide, intertwine, operate in parallel, or speak past each other in ways that often marginalize Inuit and other indigenous ways of knowing and being. Inheriting waste is more than just a relay of potentially indestructible waste materials from past to present to future: through waste, we bequeath a set of politically, historically, and materially constituted relations, structures, norms, and practices with which future generations must engage.
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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 | 0.003 | 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 | 0.014 | 0.082 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".