Colonialism, Domestication, & Extinction: A Pre-Mortem for Our Ecological Futures
Bibliographic record
Abstract
This paper engages with Ghassan Hage’s concepts of ‘ungovernable waste’ and ‘generalized domestication’ to think critically about the sociopolitical position and futures of farmed animals in the context of ongoing climate and ecological crises. Against the erasure of farmed animal subjectivities, we posit that there is much to learn by turning to farmed animals as sources of wisdom, as unique knowers with lessons to teach us about extinction. We consider how Andil Gosine’s radical suggestion to embrace animality as a refusal of the civilizing discourses of colonialism, and as an act of solidarity with nonhuman animals, constitutes a critical step towards realizing multispecies justice and a move towards interspecies solidarity with farmed animals. Here Gosine provokes us to reconsider our attitudes towards animals facing extinction in varying contexts under colonial-capitalism.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.044 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".