Our Home on Native Land: Navigating Tensions between Reconciliation and the Liberal Democratic State
Bibliographic record
Abstract
Historically, reconciliation has helped states transition from authoritarian regimes to democratic regimes after a period of violent conflict. More recently, settler states, including Canada, have adopted this approach to try to heal relationships between settler and Indigenous populations. How reconciliation can be used in a non-transitional setting (in an already-established democracy), however, is uncertain. As such, this thesis analyzes points of tension between liberal democratic principles and reconciliation, focusing on liberal individualism, private property, political institutions, and multiculturalism. I then offer a reconceptualization of reconciliation informed by the work of Hannah Arendt to clarify the role of forgiveness, show reconciliation as relational, and introduce non-reconciliation as a genuine possibility. The thesis ends by scrutinizing the role that private property and political institutions play in themselves creating roadblocks on a path toward reconciliation. Ultimately, my argument is twofold. First, I argue that reconciliation is not suitable for the Canadian context when defined traditionally, and that Canadian liberal democratic principles must also be subject to change, adaptation, or removal. Second, I argue that substantive reconciliation will only come about through a radical and fundamental shift in Indigenous-settler relations that allows for the emergence of Indigenous sovereignty and puts an end to the power and control that the Canadian state currently exerts over Indigenous nations.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.052 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".