Disentangling Eudaemonia-focused Design as a Means of Flourishing Curation
Bibliographic record
Abstract
The connection between humans and their homes is one that has been documented for centuries. However, the extent to which our built environments impact human physical, mental, and social health was not fully understood by the general public until the COVID-19 pandemic made this topic one of necessity and, therefore, everyday discourse. One group that was impacted most extremely by the pandemic was the older adult community. The loneliness epidemic that had begun pre-COVID was exacerbated by widespread quarantine mandates—ones especially common in countries like Australia. This older demographic needed not only to occupy home environments that supported their needs and desires but also to be meaningfully engaged during these isolating times. This presentation shares findings based on PhD research conducted in Australia in 2021, at a time when older adults were experiencing isolation during still-prevalent periods of lockdown throughout the country. It explores how intentional and fun creative activities were conducted virtually with older adults at home to engage participants remotely for the purpose of disentangling complex subjects relating to Human Building Interaction (specifically, older adult occupants, homes, and smart home technologies) and the emotional aspects of past, present, and desired future homes. The research was based on the premise of designing for the positive psychology construct of Aristotle’s eudaemonia—an interpretation of flourishing health, synonymous with being one’s best self—by considering an idyllic thriving future in addition to the tenets of self-determination theory, namely autonomy, competence, and relatedness. The art of exploring tangible design activities while considering eudaemonia leisurely at home resulted in the older adults identifying eudaemonic home design principles as planned as well as experiencing unexpected motivation, making improvements in their spaces and lives. The research contributes to knowledge about architectural design elements that cultivate flourishing health and well-being at home but also informs design praxis—underscoring how intentional design done even virtually has the potential to uncomplicate abstract or delicate subject matter, improve research and design experiences and prompt the realisation of people’s best selves.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".