Bibliographic record
Abstract
Purpose: This paper explores the underlying forces, specifically the “land lifeworlds” behind land-use laws, at the heart of land-use conflicts between the Ontario government and Indigenous communities. Approach: I examine the research of Anishinaabe and Canadian legal scholars on the “land lifeworlds” or ethics underlying Anishinaabe and Canadian land-use law. This research takes the form of anthropological observation, historical analysis of the formation of property law, and close textual analysis of key legal documents. I then apply this research to observe the role these land lifeworlds play in a particular land-use conflict case study. Results: The land lifeworlds underlying the actors’ land-use laws are fundamentally opposed. The lifeworld underlying Ontario land-use law prioritizes an ownership-exploitative relationship to the land. In contrast, the land lifeworld of Anishinaabe law advocates a reciprocal relationship to the land, where the land is envisioned as a member of the community deserving of the highest respect. Regarding the case study, the opposing nature of these two lifeworlds manifests itself in the non-recognition of an Ontario judge toward the legitimacy of the Anishinaabe stewardship position. Conclusion: These results suggest a possible path toward a more just resolution of land-use conflicts between Indigenous communities and the Ontario government: the provincial government must make a fundamental, not merely surface level, change in its land-use policy. This means changing the land lifeworld underlying land-use law such that a reciprocal relationship with the land as a moral agent worthy of rights can be recognized as legitimate.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.083 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".