Time Grows on Trees: The Effect of Nature Settings on Time Perception
Bibliographic record
Abstract
Time perception may vary depending on one's surroundings.Four studies examined whether time feels slower in nature compared to urban settings.Participants viewed images of nature or urban settings (Study 1), viewed a video of a walk through a forest or city via virtual reality headsets (Study 2), imagined themselves walking down a forest path or a city street (Study 3), and actually walked by a river or through campus tunnels (Study 4).Time perception was measured through subjective duration estimates (Study 1, 2, 3, 4) and objective duration estimates in minutes/seconds (Study 1, 2, 4).Across studies, the surroundings affected time estimates.Participants estimated the objective duration (Study 4) and subjective duration (Study 2, 3, 4) of the nature stimuli as significantly longer than urban stimuli.This research contributes to both time perception and environmental literature and may be applied in everyday time management.
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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 | 0.012 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".