Varieties of value: Children differentiate caring from liking
Bibliographic record
Abstract
Liking one object more than another does not guarantee caring about it more, and vice-versa. Here we show that with age, children increasingly distinguish between these two ways of valuing objects. We conducted three experiments on 589 children and 415 adults. In Experiment 1, 3–7-year-olds and adults chose between their own plain sticker and another more attractive one. Among 6−7-year-olds and adults, choices of the plain sticker were relatively more common for caring than liking. In Experiment 2, 3−6-year-olds and adults inferred what others care about and like. Among 4−6-year-olds and adults, choices of a plain object owned by another person were relatively more common in inferences about caring than liking. However, children chose the owned objects at low rates, raising the possibility that children had predominantly based judgments on the relative attractiveness of the objects. Experiment 3 addressed this concern by examining judgments about identical-looking objects.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".