Exploring Sustainable and Culturally Appropriate Solutions Through the Mino Bimaadiziwin Partnership
Bibliographic record
Abstract
The First Nations communities of Northern Manitoba, Canada, have been facing an extreme housing crisis. Overcrowding paired with insufficient funding, low-quality materials and mould contamination has created an uninhabitable environment where hepatitis, acute rheumatic fever, asthma, and tuberculosis are nine times more prevalent on remote northern reserves. Given that adequate shelter is considered one of the fundamental requirements of life, the circumstances seen on reserves are unacceptable. This Master of Interior Design Practicum project explores how to address the housing crisis through a series of literature reviews, precedent analysis and firsthand experience building in remote First Nations communities. Research begins with recognizing one's problematic inherited Western Bias, a critical starting point when organizing a culturally oriented design framework. Literature is further explored to define Indigenous design and architecture, creating the foundation for a culturally appropriate housing solution to build on. The honourable harvest and resilient design concepts uncover ways to build homes that sustain the people living within them and sustain the land from which the raw materials are harvested. The complexity that is homeownership on-reserve is addressed as building strategies and energy independence contributes to self-determination. Additionally, the lessons learned from historical and modern Indigenous home design ground findings from literature in real-life housing solutions. Looking into a wide range of Indigenous housing solutions helps bridge the gap between traditional ways of knowing and modern schools of thought. Lastly, designing and building in remote First Nations communities with the Mino Bimaaiziwin Partnership has been an all-encompassing learning experience that has shaped all aspects of the design process and outcomes. This unique and life-changing opportunity completely reformed how I now approach design, my relationship with the earth and the ongoing effort to reconciliation.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".