An architectural design framework to promote healthy indoor-outdoor connections in Arctic housing
Bibliographic record
Abstract
This research proposes biophilic intermediate spaces as a promising architectural solution to improve indoor-outdoor connections, occupant well-being, and energy efficiency in Arctic housing. Basic examples of intermediate spaces in Arctic housing models include porches and vestibules. However, the architecture of these spaces has not yet been optimized to adress extreme climatic conditions and occupants’ needs. Therefore, this research develops an architectural design framework to optimize the architecture of intermediate spaces for Arctic housing to meet occupants’ well-being needs and improve housing energy efficiency. The research methodology combines an archetypal approach, exploratory case study analysis, and scoping literature review. The archetypal study examines the historical development of Canadian Arctic housing models in Nunavut, revealing the typological evolution, features, potentials, and deficiencies of intermediate spaces in the Arctic. The study identifies of the main design variables and performance indicators of intermediate spaces corresponding to healthy and positive indoor-outdoor connections, thermal and visual comfort, and energy efficiency. A conceptual model of an intermediate space is then simulated as an exploratory case study for a public Canadian Arctic residential building. The architectural design framework is established based on findings from the literature, archetypal studies of Arctic housing, and simulation results of an integrated model for an intermediate space and a public Arctic housing model in Nunavut. The proposed framework includes main architectural variables such as physical adjacency, material, orientation, space depth, and transparency ratio which impact thermal, lighting, and energy performance. This design framework can serve as a reference for creating policies and decision-making processes that integrate biophilic intermediate spaces with Arctic building practices, contributing to Canada's strategic plan for energy efficiency and vegetable production in the Arctic.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".