Restoring human and more-than-human relations in toxic riskscapes: “in perpetuity” within Lake Superior’s Keweenaw Bay Indian Community, Sand Point
Bibliographic record
Abstract
Lake Superior’s Keweenaw Bay is the ancestral and contemporary homeland of the Anishinaabe Ojibwa and their relatives. It is also a toxic riskscape: Its waters, shorelines, and fish beings are polluted by an unknown tonnage of legacy mining waste rock called “stamp sands,” which contain unsafe levels of toxic compounds. This paper describes Ojibwa stewardship principles and reciprocal obligations, illustrating First Treaty With Gichi-Manitou practices of restoring relations within a toxic riskscape. Defined here, riskscapes are places and spaces where pollution/toxicity relations are continually reconfigured in literal, symbolic, and systemic ways. We share a story from Keweenaw Bay’s Sand Point restoration project (2002–present) to elucidate distinctly different approaches and challenges to restoring ecological relationships, including those between human and more-than-human beings. The restoration of 35 acres of barren shoreline into a thriving landscape concurrently created space for reclaiming Ojibwa stewardship obligations to land, water, and life. The goal was to restore Sand Point as a self-sustaining plant community, but maintenance remains demanding and costly. Lake Superior forces continually mobilize stamp sands, and recent extreme storm events have done so with even greater force. Thus measures of “success” are reconsidered annually, a reminder that “in perpetuity” toxic governance regimes are as unstable as riskscapes themselves. Yet Sand Point is a story of hope. Substantial transformations atop the surface reflect the restoration of many relationships between communities, institutional partners, and more-than-human beings. It is our Sand Point plant relatives who share the most valuable lessons of restoring sustainable livelihoods: resilience is inter-dependent communities caring for one another.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".