Negative Affectivity Predicts Individual Differences in Decision Making for Preschoolers
Bibliographic record
Abstract
The authors' goal in conducting this study was to explore the association between temperament and future-oriented decision making. Forty-three preschoolers (mean age = 51 months) were given a child variant of the Iowa Gambling Task (IGT) and asked to choose between a deck with higher immediate rewards and a deck with higher future rewards. Children who were higher on the Extraversion/Surgency factor of the Child Behavior Questionnaire chose more frequently from the higher immediate rewards deck early in the game. The externalizing dimension of Negative Affectivity (anger/frustration, soothability and discomfort) made the greatest contribution to prediction of performance in the last block of the game. Children who were more easily frustrated and had difficulty regulating negative emotions chose more from the deck with higher immediate rewards. There was a significant interaction between the externalizing dimension of Negative Affectivity, the internalizing dimension of Negative Affectivity (sadness and fear) and Extraversion/Surgency on the last block. These results suggest a complex association between IGT performance and temperament in preschoolers.
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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 | 0.002 |
| 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) | 0.002 | 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".