Witnessing the Colonialscape: lighting the intimate fires of Indigenous legal pluralism
Bibliographic record
Abstract
Law has been used to impose and enforce colonial power relations in Canada, as well as being used as a tool of resistance within Indigenous-state relations. The day-to-day lives of Indigenous people remain shaped by the foundational geo-legal construction of Indians and Indian reserves through which the violence of settlement has been neutralized. Yet Indigenous law and Indigenous geographies continue to produce their own socio-legal identities and territories of meaning, which exist alongside colonial ideas about Indians and Indian space. Working from the understanding that Canada is a legally pluralistic state, it follows that the legal consciousness of Indigenous people are formed within relationships to multiple legal orders, and the individual identities of Indigenous people are produced through these heterogeneous relationships. In this dissertation, a grounded analysis of legal pluralism emerges as I investigate dynamics of law, violence and space through the frequently unheard perspectives of Indigenous people working to address violence in communities across BC. Although widespread efforts have been undertaken to seek justice for offences against native people, violence continues to be a daily reality for Indigenous people across BC and Canada. Thus, I first examine several cases of violence which have emerged into public discourse in recent years, asking what has been accomplished in these efforts to gain social and legal recognition of violence. Second, efforts to address violence within Indigenous communities are explored, suggesting that these initiatives at community, family and interpersonal scales might be understood as expressions of Indigenous law. These diverse initiatives are changing norms around violence at a community level among networks of people who share a reciprocal sense of responsibility to one another, rooted in Indigenous territorialities. These efforts to address violence form a countermeasure to the violence of Canadian law, providing possibilities for engagement of individual and collective agency, power, and self-determination. I conclude by discussing how the recognition of Indigenous jurisdiction opens up the possibility for Indigenous people to escape justice wormholes, recategorizing themselves and the violence against them within Indigenous geographies of law rooted in intimacy rather than violence.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.045 | 0.078 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.009 |
| 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".