The physiological and psychological impact of boring buildings: field studies of the effects of architectural façade complexity
Bibliographic record
Abstract
People who live and work in urban environments pass by countless buildings daily. The design of these buildings can influence their day-to-day experiences. Visual complexity is an important feature of buildings, influencing aesthetic appreciation. But beyond aesthetic judgments, how does the design of building facades affect people’s experiences? To answer this question, we conducted field studies in London and Toronto (n=97) measuring the physiological and affective effects of viewing buildings varying in façade complexity. We brought participants for walks through each city, stopping in front of pre-selected buildings for five minutes while measuring skin conductance – a measure of physiological arousal - along with standard questionnaires. Our results showed that façade complexity significantly impacted people’s physiological states. Low complexity buildings were associated with a significant decrease in skin conductance over time, compared to high complexity buildings. Low complexity buildings were perceived to be highly boring and unattractive, while high complexity buildings were rated as being interesting and attractive. Our findings demonstrate that boring, low complexity buildings are not merely an aesthetic concern – they can affect people at a raw, physiological level.
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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 | 0.001 |
| 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) | 0.002 | 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".