Exposure to High-Rise Buildings Negatively Influences Affect: Evidence from Real World and 360-degree Video
Bibliographic record
Abstract
Cities are densifying at a rapid rate, and accordingly, are constructing high-rise buildings to accommodate more people. The aim of this study was to quantify the physiological and psychological impacts of being in the presence of high-rise buildings in Central London, in a real and virtual 360-degree video environment. Using a within-subjects design, participants were exposed to a low-rise and high-rise building. While exposed, participants were monitored for electrodermal activity. They were also administered the Self-Assessment Manikin measure and a cognitive appraisal questionnaire. Participants rated the high-rise building environment to be less open, less friendly and rated themselves to feel less happy and have less sense of control, as compared to low-rise buildings. We found these effects in both the real world (n = 16) and a 360-degree video setting (n = 121). These findings suggest that city environments populated with high-rise buildings can have negative impacts on urban dwellers. Furthermore, this study provides a methodology to examine how individuals respond to the built environment and stands to inform urban design and architectural practices.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".