Emotions before actions: When children see costs as causal
Bibliographic record
Abstract
Adults expect people to be biased by sunk costs, but young children do not. We tested between two accounts for why children overlook the sunk cost bias. On one account, children do not see sunk costs as causal. The other account posits that children see sunk costs as causal, but unlike adults, think future actions cannot make up for sunk costs. These accounts make opposing predictions about whether children should see sunk costs as affecting emotions. Across three experiments, 4-7-year-olds (total N = 320) and adults (total N = 429) saw stories about characters who collected items that were easy or difficult to obtain, and predicted characters' emotions and actions. At all ages, participants anticipated that characters would feel sadder about high-cost objects, but only adults predicted that characters would keep high-cost objects. Our findings show that children see incurred costs as causal, and that costs are integrated children's and adults' theory of emotions. Moreover, the findings suggest that developmental differences in sunk cost reasoning may rest in children's incomplete mental accounting. We also discuss children's reasoning about rational and irrational action.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.019 |
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; both teacher heads agree on what is shown here.
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".