Anchored in the present: Preschoolers more accurately infer their futures when confronted with their pasts
Bibliographic record
Abstract
People often speculate about what the future holds. They wonder what will happen tomorrow, and what the world will be like in the distant future. Nonetheless, people's ability to consider future possibilities may be restricted when they consider their own futures. Adults show the ‘end of history’ illusion, believing they have changed more in the past than they will in the future. Further, preschoolers are even more limited in anticipating future change, as 3-year-olds insist their current desires will persist later in life. These findings suggest a deficit in children's and adults' abilities to simulate alternative possibilities that pertain to themselves. However, we report four experiments (n = 233) suggesting otherwise, at least for children. We find that 3-year-olds accurately infer their futures when prompted to consider their past rather than present preferences. Children also succeed at inferring their past preferences when not shown items they currently prefer. This shows that children can reason about their pasts and futures, though this ability is hindered when they are shown items that anchor them to the present. Our findings suggest that children's difficulties with mental time travel reflect a failure to shift away from the present rather than an inability to simulate alternative possibilities.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".