Oh … so close! Children’s close counterfactual reasoning and emotion inferences.
Bibliographic record
Abstract
= 227, Experiment 4) consider close counterfactual alternatives when inferring other people's emotions. In Experiment 1, 6-year-olds (but not 4- and 5-year-olds) inferred that an agent would feel sadder about winning a mediocre prize if she later found out that a more attractive one could have easily been won. However, children of all ages failed to judge whether the better outcome could have easily happened. In Experiment 2, when 5- and 6-year-olds knew the locations of the prizes beforehand, they inferred that an agent would be equally happy about winning a mediocre prize, regardless if she almost won a better prize or not. Again, they did not recognize when the better outcome was a close counterfactual possibility. In Experiment 3, we included extra cues to the closeness of the alternative and both 5- and 6-year-olds inferred that she would feel sadder about winning a mediocre prize, and 6-year-olds acknowledged that the attractive prize was a close counterfactual alternative. In Experiment 4, adults considered close counterfactuals when inferring emotions. Our findings suggest that close counterfactuals influence children's emotion inferences before they become able to acknowledge their closeness. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.002 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".