Porcupine and Other Stories: Legal Relations in Secwépemculecw
Bibliographic record
Abstract
For thousands of years, Secwépemc laws (like other Indigenous laws) related to the Secwépemc lands, or “Secwépemcúlecw,” developed and were learned and practiced within a context where the personhood of Secwépemc individuals, as well as animals and the earth itself, was not in dispute. Nor was the existence, legitimacy or efficacy of Secwépemc laws. All of these crucial legal relationships still exist, and are ongoing. However, for the past 150 years or so, Secwépemc laws, and people, have lived in relation to something quite distinct — a set of laws that were jurispathic in nature —laws that would not recognize or tolerate any other law but themselves. The Secwépemc Nation’s resilience and perseverance in upholding and revitalizing Secwépemc laws in the face of this colonial disregard, attests to their strength and enduring value. In this article, the authors discuss the purpose, as well as some of the methods, outcomes and limits of the Secwépemc Lands and Resources Laws project produced in collaboration with the University of Victoria Indigenous Law Research Unit. They then examine present interactions between Secwépemc and state land and resources laws operating within Secwépemcúlecw, including the challenges and limited opportunities that exist within the way these legal and political relations are currently structured and implemented on the ground. Finally, they draw on the Secwépemc “Story of Porcupine” to suggest a constructive way forward towards a more mutually respectful Nation-to-Nation relationship between the Secwépemc people and the Canadian State.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.034 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".