A Preliminary Study of 3D Printing Home Designs for Improving Efficiency and Sustainability of Indigenous Housing in Canada
Bibliographic record
Abstract
Canada has been experiencing a significant housing crisis in recent years, especially in remote and Indigenous communities, yet most of the existing construction approaches have not been rapid, sustainable, and affordable enough to meet community needs. To address this challenge, this study explores the feasibility of 3D printed (3DP) housing and develops a design that is informed by Indigenous housing requirements and is realized through a physical design prototype tailored for the implementation of 3DP homes. Site visits and community engagement were integral parts of the research to help deliver invaluable insights that guided the design process, ensuring cultural sensitivity and inclusivity. The prototyped 3DP design offers efficient and sustainable solutions customized to the unique cultural and climatic needs of Indigenous communities in Canada. The final 3DP design seamlessly integrates traditional Indigenous architectural elements, such as a circular shape inspired by pit houses, with modern construction techniques, yielding a flexible, sustainable, and culturally pertinent home design. Future research work will be focused on how the proposed 3DP design can be adapted to enable mass customization to accommodate the diverse needs and preferences of Indigenous communities across Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".