Effects of practicing episodic versus scripted recall on children's subsequent narratives of a repeated event.
Bibliographic record
Abstract
Children (N = 240) ages 5 to 8 years participated in 1 or 4 activity sessions involving interactive tasks (e.g., completing a puzzle); children with single-event participation served as a control group. One week after their last/only session, all children were practiced in episodic recall of unrelated experiences by asking about either the (a) a single-experience event, (b) a specific instance of a repeated event, or (c) scripted recall of a series of events. Children were subsequently interviewed in an open-ended, nonsuggestive manner about 1 of the activity sessions; children with repeated experience were permitted to nominate the session they wanted to talk about. For children who participated 4 times, practice recalling a specific instance benefited 5- and 6-year-old children most; they reported more target details than other conditions and showed awareness of the repeated nature of the activity sessions. Accuracy levels were maintained regardless of practice type. Children with single-event experience were largely unaffected by manipulation of practice condition. Practical implications for interviews with child victim/witnesses and theoretical implications on children's ability to recall specific incidents of repeated events are discussed. © 2011 American Psychological Association.
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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 | 0.030 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".