Bibliographic record
Abstract
People are sometimes drawn to novel items, but other times prefer familiar ones. In the present research we show, though, that both children’s and adults’ preferences for novel versus familiar items depend on their goals. Across four experiments, we showed 4- to 7-year-olds (total N = 498) and adults (total N = 659) pairs of artifacts where one was familiar and the other was novel (e.g., a four-legged chair and ten-legged chair). In Experiment 1, children wanted to have familiar artifacts, but to learn about novel ones. Experiment 2 replicated this pattern using a simpler procedure, and found the same pattern in adults. In Experiment 3, 4- to 6-year-olds and adults more strongly preferred familiar items when choosing which they would rather have than when choosing which they would rather try using. Finally, Experiment 4 replicated adults’ preferences to have familiar items and learn about novel ones with an additional set of items. Together these findings show that preferences for novelty depend on people’s goals. We suggest these effects arise because children and adults are motivated both by the promise of information and the desire for safe options in high commitment decisions that entail risk.
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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Research integrity | 0.001 | 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".