Wellness architecture: the magnitude of spatial healing of wellness in workplace culture
Bibliographic record
Abstract
This study focuses on to the needs of the new generation entering the workforce, with the intention of prioritizing their wellbeing and offering a space that represents work-life balance. It takes on a building at 205 Yonge Street, formerly owned and \noccupied by the Toronto Dominion’s Bank in Toronto’s Financial and Entertainment District, as a theoretical model for an \nadaptive reuse project that serves the broader creative community. \nHow can architecture support mental illness and physical wellness in the new workplace? \nThis thesis explores existing knowledge and theory regarding human well-being and the fundamental shifts of workplace \nculture. Through a series of case studies, it analyzes office designs and their correlation to health. This research seeks to gain an \nunderstanding of the body’s relationship to the spatial environment, specifically body movement, the configuration of furniture \nand the quality of space. By analyzing and synthesizing existing theories and data, the theoretical model demonstrates the \npotential of new workplace designs to improve physical and mental wellness. The outcome of this thesis is the re-imagination \nof an inclusive workplace culture that fosters wellness by emphasizing a sense of community among professionals.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| 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".