An architectural insight into the role of personalisation of homes and its effects on residents’ psychological well-being
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the importance of personalisation in the relationship between the architectural design of homes and inhabitants’ psychological well-being. Design/methodology/approach This interdisciplinary mixed-method study first investigates the existence of a link between personalisation and users’ association with home through a quantitative study (n = 101) and then explores the nature of this relationship through qualitative interviews (n = 13) in a sequential explanatory approach. Findings The main findings of the study highlight the significance of personalisation in relation to the way people perceive home. A direct link was established between participants’ involvement in the transformation of the home and their satisfaction with the residence, as well as satisfaction with life in general. Further thematic analysis of the qualitative study revealed further conceptualisations of personalisation, which together form an umbrella concept called transformability. Research limitations/implications The findings underscore the need for embedding flexibility as an architectural concept in the design of residential buildings for improving the well-being of occupants. Originality/value The design of homes has a great impact on inhabitants’ psychological well-being. This is becoming of greater importance in light of the global COVID-19 pandemic that has led to an increase in the amount of time spent in homes. This research contributes to this debate by proposing concepts for a deeper understanding of architectural influences on the psychology of the home.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".