Including Indigenous perspectives in policy-making processes: natural resource development in Northern Ontario
Bibliographic record
Abstract
This research seeks to understand the experience of the Atikameksheng Anishnawbek with the Ontario Government, specifically with consultation on legislation pertaining to natural resource development (NRD). It also seeks to build an understanding of whether or not the experiences of Atikameksheng, an Anishnawbek Nation whose territory includes the Sudbury Basin, are applicable to NRD policy-making contexts surrounding Indigenous communities in Treaty 9 near the Ring of Fire. The Ring of Fire is located in remote Cree and Ojibway territories in the Northwest of Ontario. Economic and environmental interests there have resulted in new legislation for natural resource development and land-use management and these remote First Nations are having to interact with the resource development sector for the first time. Following an Indigenous research methodology based on Anishnawbek relationship building principles, qualitative data was collected via semi-structured interviews. Participants came from three groups: Atikameksheng Anishnawbek employees and community members, Ontario Government employees, and/or a mining company. There were five participants in total. Key informant interviews with research participants established that there is a clear gap in terms of consultation for legislative policy making. It is commonly misunderstood that consultation is continually occurring within the NRD sector as it is only happening formally for specific projects, but not for the development of legislation that mandates consultation. The results of this research suggest that the demands of regulatory and consultation processes established by the Crown do not align with the expectations of First Nations. These demands often also outweigh the required resources available for First Nations to effectively participate in this engagement.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.025 | 0.016 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".