Agonistic reconciliation: inclusion, decolonisation and the need for radical innovation
Bibliographic record
Abstract
In settler colonial societies like Australia, Canada, New Zealand and the United States, Indigenous–state relations are defined by ongoing conflict over unresolved questions of sovereignty, self-determination, and land. These conflicts have remained intractable regardless of the policy approaches engineered by the state. This article outlines an analytical approach to agonistic reconciliation by mapping the polar ends of a spectrum of responses to conflict in Indigenous–settler relations, with inclusion at one end of this spectrum and decolonisation at the other. Agonistic inclusion seeks to engage reconciliatory relations within colonial democratic institutions, while agonistic decolonisation rejects the legitimacy of these institutions and seeks radical innovation in their place. The article concludes by arguing that scholars must be alert to the seductive pull of inclusion and push instead towards the radical innovation that decolonisation demands.
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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 | 0.026 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.117 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.006 | 0.006 |
| 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".