Against ontological capture: Drawing lessons from Amazonian Kichwa relationality
Bibliographic record
Abstract
Abstract This article offers an experiment in theorising within or across a ‘space’ of ontological disagreement – which, as numerous authors have contended, characterises much that is at stake in relations between states and Indigenous peoples in the Americas. Such ontological disagreements, I argue, contain radical potential for disrupting globally dominant and anthropocentric patterns of thinking and relating, and for generating alternatives. I substantiate this point with reference to the relational ontologies informing different Indigenous ways of analysing and practicing existence. Drawing on Amazonian Kichwa thinking and Anishinaabe accounts of treaties, I show how these relational ontologies recast the problem of how it is possible to relate with difference, in such a way as to fold an inter-human ‘international’ into a continuum of relations that include human-nonhuman ones. Distinct normative horizons emerge. I argue that non-Indigenous people can draw a range of provocations here concerning our constitution as selves and the political space in which we understand ourselves to possibly participate. I also claim, however, that this more transformative potential is predominantly squandered through processes of what I call ontological capture, which troublingly re-entrench dominant construals of reality and forestall a more radical questioning and re-patterning of accompanying lifeways.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".