Mino Bimaadiziwin Homebuilder Program’s Impact on Sustainable Livelihoods Among Youth in Garden Hill and Wasagamack First Nations: An Evaluative Study
Bibliographic record
Abstract
The Mino Bimaadiziwin Homebuilders postsecondary education pilot project built Indigenous youth capacity and houses in two remote Anishinini reserves—Garden Hill and Wasagamack. To evaluate this community-led project, a sustainable livelihood assessment holistically measured the impact on 45 of the 70 (64%) Homebuilder students and the community. The community benefited by gaining three culturally appropriate houses built from local lumber and employment opportunities for Anishinini instructors. A longitudinal survey found five of the six livelihood assets improved statistically and significantly, including satisfaction with social relationships, cultural awareness, income and ability to pay bills, housing safety, and human development. Students reported better relations with their families and neighbourhood. Most (85%) of the 70 Homebuilder students earned postsecondary certificates either in forestry, homebuilding or both while obtaining a training stipend, which elevated their incomes. These positive outcomes occurred despite project underfunding, the COVID-19 pandemic lockdown, climate change events, and inequitable housing policies under the Indian Act. Based on this project’s success, we recommend investing in Indigenous-led postsecondary education in community homebuilding projects. However, to attain equitable housing and human rights, a plan is needed to overturn the Indian Act, which keeps Indigenous people as “wards of the state” and their land in trust.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".