Learning, Living, and Teaching Anishinaabe Law: A Tribute to Jean Borrows
Bibliographic record
Abstract
Indigenous Elders are vital to the transmission of Indigenous laws. This article describes the role of one Elder’s contribution to legal education, both within her community and to the Canadian legal academy more generally. Jean Borrows is an Anishinaabe women and a member of the Chippewas of the Nawash First Nation in what is now called Ontario, Canada. This article’s focus on her influence helps define, and potentially expand, the question: what is the Canadian legal academy? Indigenous Elders teach law through the way in which they live their lives and through the words that they impart to others. Borrows has carried many responsibilities over her long lifetime, which have helped her practise and pass along her community’s legal traditions. She has been a hunter, angler, forager, entrepreneur, Indian day school student, real estate agent, member of the Chippewas of Nawash First Nation, professor of Anishinaabe law, and N’okomis (my grandmother), to name a few. Indigenous legal orders, like those lived by Jean, have always informed the Canadian legal landscape, and they continue to do so in dynamic ways. Yet there are challenges to recognizing community-based professors of Indigenous law. By sharing select stories of Borrows’s life, this article suggests that the Canadian legal academy is not merely confined to university law faculties because Indigenous law teachers and theorists also live in community contexts. I aim to show how Borrows’s varied responsibilities, experiences, and teachers throughout her life gave her a type of legal knowledge that led her to become an influential educator of Anishinaabe law, including as an Elder at the land-based Anishinaabe Law Camps hosted regularly in her community since 2014 for hundreds of juris doctor students.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| 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".