Time spent imagining does not influence younger and older adults’ episodic simulation of helping behavior
Bibliographic record
Abstract
Shared cognitive processes underlie our ability to remember the past (i.e., episodic memory) and imagine the future (i.e., episodic simulation) and age-related declines in episodic memory are also noted when simulating future scenarios. Given older adults' reduced cognitive control and protracted memory retrieval time, we examined whether imposing time limits on episodic simulation of future helping scenarios affects younger and older adults' willingness to help, phenomenological experience, and the type of details produced. Relative to a control task, episodic simulation increased younger and older participants' willingness to help, scene vividness, and perspective-taking regardless of the time spent imagining future helping scenarios. Notably, time spent imagining influenced the number, but not proportion of internal details produced, suggesting that participants' use of episodic-like information remained consistent regardless of the time they spent imagining. The present findings highlight the importance of collecting phenomenological experience when assessing episodic simulation abilities across the lifespan.
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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 | 0.000 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".