Putting time in perspective: How and why construal level buffers the relationship between wait time and aggressive tendencies
Bibliographic record
Abstract
Summary We spend a substantial part of our daily life waiting, and unfortunately, wait time can fuel aggressive tendencies. Our study examines the relationship between wait time, perceived wait time, and aggressive tendencies from a construal level perspective. In Study 1, we found that the higher the construal level, the stronger the relationship between actual and perceived wait time and the stronger relationship between perceived wait time and aggressive tendencies. In Study 2, we manipulated construal level and found that power explains the moderating impact of construal on the wait—aggressive tendencies relationships. Results demonstrate the role of construal in explaining both perceived wait time and aggressive responses to long wait times, suggesting that mental construal influences both the psychological experience of time and the subsequent reaction to that experience. Overall, these results contribute to research on subjective time perspective by enhancing the knowledge and understanding of the determinants and effects of perceived wait time.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".