Changes in the experience of time: The impact of spatial information on the perception and memory of duration
Bibliographic record
Abstract
Although it is understood that our experience of time is fluid and subjective, the cognitive mechanisms underlying this phenomenon are not well described. Based on event segmentation theory, we tested the hypothesis that changes in the context, particularly the spatial context, of an experience impact how an individual perceives (encodes) and remembers the length of that event. A group of participants viewed short videos of scenes from movies that either contained shifts in spatial context (e.g., characters moving through doorways) or did not contain any shifts in spatial context. In one task, participants estimated a randomly selected time duration (between 10 and 23 s) when encoding these videos. In a second task, the same participants estimated the duration of the videos after viewing them. We found that even though the presence of spatial shifts impacted how time was perceived, the nature of this effect differed as a function of task. Specifically, when time was estimated at encoding, these estimates were longer for videos that did not contain spatial shifts compared with those with spatial shifts. However, when these estimates were made at retrieval, durations were reported as longer for videos with spatial context shifts than those without. A second experiment replicated these main findings in a new sample. We interpret these results as providing new evidence for theories on how context changes, particularly those in spatial information, distort the experience of time differently during the encoding and retrieval phases of memory.
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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 | 0.010 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".