Integrating Indigenous Cultural Values and Sustainable Architecture for Healing and Empowerment.
Bibliographic record
Abstract
This study delves into integrating Indigenous cultural values, traditional healing practices, and sustainable architecture to create a comprehensive framework for fostering healing, reconciliation, and empowerment among homeless and vulnerable Indigenous populations in Calgary, Canada. The study adopts a collaborative approach, seeking the wisdom of Indigenous Elders and engaging with members of Siksika Housing to address housing challenges, addiction recovery, and health and emotional well-being. Central to this effort is the development of five Indigenous healing principles derived from Indigenous knowledge and health practices, that serve as design guidelines for Architects and developers for creating an Indigenous Healing Center for Indigenous peoples known as the HT-CIC principles: a holistic approach to healing, traditional healing ways, community relations, Indigenous Ceremonies, and Connection to land. These principles would guide designers to create Healing Centers rooted in Indigenous healing values. The HT-CIC principles are pillars upon which Indigenous Healing and wellness are built, offering pathways toward healing, resilience, and cultural renewal. By embracing these principles, individuals and communities can reclaim their inherent strengths, honor their cultural heritage, and embark on journeys of healing and reconciliation. The study aims not only to alleviate homelessness but also to empower individuals, fostering a holistic journey towards wellness, and self-discovery while promoting Indigenous values within a sustainable built environment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".