Ambiguity and Irreconcilability: A Critical Look at Reconciliation Discourse in Federal Land Claims and Self-Government Political Communications
Bibliographic record
Abstract
Can reconciliation be meaningful when it is at once a journey, a path, a milestone, a framework, a tool of economic development, a spirit, and a process? In this thesis, I use a multimethod approach to problematize how reconciliation discourse is employed ambiguously in both policy and practice in order to maintain settler colonial occupation of stolen Indigenous lands. I first conduct a policy review of federal land claims and self-government frameworks before turning to a Critical Discourse Analysis of public communications to illustrate the limitations of these state-led processes of reconciliation. My analysis elucidates the ways in which these processes are instantiations of settler governmentality that continue to exist as common sense (Rifkin, 2013) within a discursive framework of state-led reconciliation politics. As such, my work demonstrates that in order to work towards the bigger project of decolonization and resurgence, reconciliation must move from purely aspirational terms to substantive, treaty-based responsibilities with the repatriation of Indigenous land as its overarching, incommensurable purpose. Keywords: reconciliation politics; settler colonialism; Crown-Indigenous relations; critical policy studies; critical discourse analysis.
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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 | 0.040 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.034 | 0.135 |
| Scholarly communication | 0.027 | 0.035 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.011 | 0.011 |
| 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".