The nonhuman turn or a re-turn to animism? Valuing life along and beyond capital
Bibliographic record
Abstract
In this commentary, I point out that Büscher and other critics of the nonhuman turn ignore insights offered by Feminist, Black and Indigenous scholarship that help rethink the human and alternate worldmaking possibilities. The healthy corrective to the somewhat apolitical celebration of liveliness and entanglements in Western new materialist and posthumanism literature, that Büscher and others seek, already exists in Feminist, Black and Indigenous scholarship and practices, and in activism for environmental and climate justice around the world. In these times of deep ecological crises and precarity, we would do well to turn to the wisdom of Indigenous Peoples and other land-based cultures that embody and live by some of the central propositions of the ‘nonhuman turn’. I argue that the central propositions of nonhuman turn – relationality and interdependence; decentring and rethinking the human; honouring the agency, intelligence and subjecthood of other beings – offer alternate ways of doing politics and of imagining and enacting pluriversal, postcapitalist worlds. If this is not grounds for radical ecopolitics, then what is?
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.051 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".