Ecological restoration as Indigenous environmental justice: A case study of the Upper Great Lakes Métis in Sudbury, Ontario
Bibliographic record
Abstract
Indigenous peoples have long-standing relationships with the lands and waters in their communities and can, therefore, be disproportionately affected by the environmental impacts of resource extraction and industrial development. As such, ecological restoration offers social and environmental implications that have the potential to transform communities and promote Indigenous environmental justice. This thesis examines the relationship between ecological restoration and Indigenous environmental justice, specifically focusing on the Upper Great Lakes Métis in Sudbury, Ontario. Sudbury has a long history of mining and industrial development that has led to severe environmental degradation. However, the implementation of a successful ‘re-greening programme’ over the last four decades has remarkably restored components of Sudbury’s damaged landscapes. Despite the success of the scientifically-based restoration programme, there has been no research on how the Métis living in Sudbury perceive its processes and goals. This study seeks to fill this gap by exploring how the Métis perceive their environment and how they can contribute to restorative environmental work in the region. Using a mixed-methods approach, this study uncovers local perspectives on ecological restoration and environmental justice whilst drawing upon environmental justice frameworks, decolonising principles, and Two-Eyed Seeing. Through the use of ethnography with Métis participants and restoration professionals, the study uncovers local concerns regarding well-being and the environment. The study finds that the Upper Great Lakes Métis prefer a restoration approach incorporating Indigenous and Western scientific knowledge, underscoring the importance of Two-Eyed Seeing. This finding emphasises that acceptance of ecological restoration projects requires recognition of locally-valued forms of environmental justice. As seen in the literature, forms of justice may vary by Indigenous community. Thus, if restoration processes and outcomes are to incorporate Indigenous ways of knowing, pan-Indigenous approaches should be eschewed in favour of accommodating multiple understandings of well-being. This study contributes to Indigenous scholarship on ecological restoration and environmental justice, underscoring the importance of recognising the power dynamics between various social groups, including governments, industry, the scientific community, and other Indigenous peoples. It also highlights the need to confront these dynamics to promote Indigenous environmental justice, a concept that varies by community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".