Settler Modes of (Re)production: Indigenous Territorial Claims in Australia and Canada
Bibliographic record
Abstract
This thesis is guided by an inquiry into the state responses to Australia’s Mabo v Queensland 1992 and Canada’s Calder v British Columbia 1973 rulings in the struggle for Indigenous rights to self-government. Australia’s Cape York Peninsula and Canada’s Nisga’a Nation serve as case studies for this thesis, to answer the research questions: What consequences came out of the Mabo and Calder cases for Indigenous territorial claims in Australia and Canada? And how does the settler state reterritorialize and limit Indigenous rights to self–government? Utilizing Henri Lefebvre’s concepts of homogenization and fragmentation, this thesis finds the settler state is continuously reinventing the structures of terra nullius (vacant lands) to preserve political and economic stability. Lefebvre introduces us to the concept of reterritorialization, as state mechanisms used to reconfiguration of social, political, and economic relationships to ensure Indigenous rights to self–government are limited. In the aftermath of the Mabo and Calder decisions, this thesis traces the settler state’s mechanisms to gain political and economic certainty by removing Indigenous rights to self–government. My findings reveal Australia’s ‘bundle of rights’ approach under the Native Title Act further limits Indigenous rights of self–government relative to Canada’s comprehensive land claims process.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.015 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.007 |
| 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".