The settler-rights backlash: understanding liberal challenges to Indigenous self-determination
Bibliographic record
Abstract
In the archetypal settler-colonial states of the United States, Canada, Australia and New Zealand, Indigenous peoples have joined the ‘rights revolution’, pressing for self-determination. They have been met by a ‘settler-rights backlash’, contraposing settler and Indigenous rights. This article makes two contributions. First, it presents a scoping study of settler-rights challenges in Anglo-settler states, revealing the extent and means of the settler backlash. Second, working within mainstream Anglo-settler political theory, it theorizes settler-rights challenges, exploring what liberal principles settlers invoke, what Indigenous protections they impugn, and what contrapositions of rights ensue. This article shows settlers invoke the liberal principle of universalism to impugn Indigenous sovereignty, the liberal principle of individualism to impugn differentiated citizenship, and the liberal principle of egalitarianism to impugn Indigenous decision-making and territorial control. In doing so, this article reveals the normative dynamics and internal contradictions of settler-rights challenges. By showing the extent, dynamics and contradictions of such challenges, it is hoped to help public decision-makers better understand and resolve them.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.087 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| 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 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".