Movement legacy: a bioethical and epigenetically grounded architectural framework for healthy lifestyle change
Bibliographic record
Abstract
New research in neuroscience, environmental psychology, and \nmedicine have revealed factors in the built environment that \nimprove health, however, these are not yet widely understood or \nadopted by the design community. A novel approach that better \nleverages the scientific literature to inform design is required. \nRecent discoveries in epigenetics reveal the immense impact our \nenvironment has on intergenerational human health through the \nprocess of epigenomic editing and the resultant genetic expression. \nThis thesis argues that design and health are inextricably linked \nto bioethical questions that require deeper exploration and ought \nto compel designers to reframe their role and responsibility in \ncommunity health. A new theoretical framework is developed \nthat aligns design elements at multiple scales with evidence-based \nprinciples, which elicit positive health outcomes through increased \nphysical activity prevalence. Informed by the framework, a network \nof design interventions for Sudbury, Ontario, demonstrates how \nthe built environment can foster healthy lifestyle change.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.053 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".