Recognition, Decolonization, and the Limitations of James Tully’s Public Philosophy
Bibliographic record
Abstract
Abstract This article offers a four-part argument in favor of settlers adopting an ethics of recognition in negotiations with Indigenous peoples to support decolonization in North America. Part 1 examines theories of decolonization offered by Indigenous scholars, who show that ethical practices within Indigenous communities are necessary for decolonization. Part 2 focuses on James Tully’s revision of the liberal politics of recognition (LPR), arguing that Tully brings the LPR closer to the aims of decolonization. Part 3 argues that his innovations do not sufficiently acknowledge how inequality undermines the freedom he champions. Part 4 draws on Judith Butler’s interpretation of Hegelian recognition and Leanne Betasamosake Simpson’s idea of recognition to sketch an ethics that minimizes the inequalities of participants in the political negotiations Tully theorizes. Minimizing inequality will promote the greater freedom needed for the legitimacy of negotiations, making them a possible vehicle for decolonization.
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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 | 0.001 | 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 | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".