Distinctiveness effects in children's long-term retention.
Bibliographic record
Abstract
In 3 experiments, kindergarten and second-grade children's retention was examined in the context of 2 distinctiveness manipulations, namely, the von Restorff and bizarre imagery paradigms. Specifically, children learned lists of pictures (Experiments 1a and 1b) or interactive images (Experiment 2) and were asked to recall them 3 weeks later. In Experiments 1a and 1b, distinctiveness was manipulated perceptually (changing colors) and conceptually (changing categories or switching to a numeral), whereas in Experiment 2, distinctiveness concerned the interaction (common or bizarre) between the referents. The results showed that (a) older children retained more information than younger children, (b) younger but not older children failed to benefit from numerically distinct information, and (c) distinctiveness in other domains facilitated children's retention. These results highlight the importance of distinctive information in children's retention.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".