Awareness and Symbol Use Improves Future-Oriented Decision Making in Preschoolers
Bibliographic record
Abstract
A child version of the Iowa Gambling task was used to explore the development of decision-making during the preschool period in two experiments. One hundred eighty-one children, 3.5 and 4.5 years of age, were asked to choose between a bad deck with higher immediate but lower long-term rewards and a good deck with lower immediate but higher long-term rewards. Experiment 1 explored age differences and the association of the gambling task with a delay of gratification task. Age differences in performance were found, supporting previous findings (Kerr & Zelazo, 2004) of a development difference between 3- and 4-year-old children in future-oriented decision making. Performance on the gambling task was found to be significantly associated with delay of gratification for 3.5-year-old children only. Experiment 2 explored the effect of labeling and symbol use on performance. Although having 4.5-year-old children label decks as good or bad improved their performance on the task, this labeling had no effect on 3.5-year-old childrens performance. However, having 3.5-year-old children place a symbol representing good and bad next to the decks did improve performance, but only for those children who were able to correctly label the decks. These results suggest an interaction between conscious awareness, symbol use, and making advantageous future-oriented decisions during the preschool period.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 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".