Engaging Provincial Land Use Policy: Traplines and the Continuity of Customary Access and Decision-Making Authority in Pikangikum First Nation, Ontario
Bibliographic record
Abstract
Canadian economic development is heavily reliant on natural resources in the north, which is home to many indigenous communities. Canada is facing increasing pressure to accommodate the cultural distinctiveness of indigenous peoples, and recognize their rights to self-determination within the boundaries of the state. This thesis investigates the customary land use system of Pikangikum First Nation in northwestern Ontario in the context of a community-led land use planning and resource management process, and explores the legacy and contemporary relevance of the Ontario trapline system which was introduced in 1947. Traplines represent the first intervention by the modern state in spatial organization of resource management by First Nations people outside reserves in northern Ontario. For this study, mixed methods were employed, including mapping, life history interviewing, observation in the field, and archival research. Results indicate that Pikangikum's access to resources and decision-making authority has continued to operate according to customary institutions that pre-date the traplines. While traplines were found to reduce flexibility of movement which characterized the customary system, they secured fur harvesting rights for First Nation groups, buffering Euro-Canadian encroachment on Pikangikum's traditional harvesting areas. Recent forestry activity on traplines held by Pikangikum residents indicated that traplines were no longer a sufficient buffer to intrusions. The planning initiative mandated the creation of novel community-level institutions. This process has in turn created new community-level management dilemmas, yet has had important consequences in terms of planning and management authority for Pikangikum vis-à-vis state resource management. The main theoretical contributions of this thesis relate to the commons literature, and pertain both to strategic territorial robustness to interventions of the state and outside intruders, and to moral economic dimensions of community-managed commons undergoing rapid change.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".