Anishinaabe Governance and the Commons: The Whitefeather Forest Initiative for Community Economic Renewal
Bibliographic record
Abstract
"Community-based land use planning has opened up opportunities for indigenous communities to develop resource management activities based on their values and institutions. Many traditional land-use activities of indigenous communities have been identified with complex common property systems. I present a case study which explores the commons system of Pikangikum First Nation, an Anishinaabe community in Ontario, Canada. The objectives of this paper are 1) to identify salient aspects of the traditional governance system of Pikangikum, relating to activities on the land, and 2) to analyze the adaptability of land-use institutions within the scope of a new land-use planning approach. Property rights and management of local resources can be objects of struggles with state resource management agencies. When traplines were registered in Pikangikum, First Nations people were confronted with a new system of rules introduced by the government. However, trappers continued to practice trapping, hunting, and fishing using customary institutions and values rooted in their traditional family areas. Findings were that while boundaries between traplines figured prominently in the introduced system, adaptability and fluidity of movement of Pikangikum people across these boundaries was maintained through Pikangikum social values and institutions. The tenure of traplines held by Pikangikum people is understood by them to prevent incursion by resource developers from outside, as well as to represent an understanding between the community and the resource management agency regarding traditional forms of spatial authority for land-based activities."
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".