Home Use and Experience during COVID-19 in London: Problems of Housing Quality and Design
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
COVID-19 lockdowns led to a reassessment of housing conditions and created greater awareness of their impact on wellbeing and inequalities. Changes in home use and lived experience during the pandemic were studied through a survey of London residents (n = 1250) in 2021, focusing on issues of housing design, perceptions of housing quality, and future housing expectations. The survey found that a quarter of all dwellings and at least one room in a third of homes were deemed too small and failing to meet the needs of occupants. Renters with a shortage of space and poorly maintained or designed homes suffered most. A total of 37.9% of respondents reported that their wellbeing was affected by housing conditions. While for well-designed homes aspects of dwelling size were considered the highest priority, dwelling layout, usability, adaptability, and flexibility were equally key concerns. However, how problems of housing design, quality, and size are understood often depends on highly individual experiences and expectations. By highlighting the importance of lived experience, the pandemic shows the limitations of current, normative design standards. Future space standards need greater flexibility in the distribution of floor areas and should consider a wider range of home uses to ensure more equitable and long-term housing provision.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it