The consistency of false suggestions moderates childrenâs reports of a single instance of a repeated event: Predicting increases and decreases in suggestibility
Bibliographic record
Abstract
Six- to 7-year-olds (N = 130) participated in classroom activities four times. The children were interviewed about the final occurrence (target event) either a week or a month later, during which half of the event items were inaccurately described. Half of these suggestions were consistent with the theme of the detail across the occurrences (e.g., always sat on a kind of floor mat) or were inconsistent (e.g., sat on a chair). When memory for the target event was tested a day later, children falsely recognized fewer inconsistent than consistent suggestions, especially compared to a control group of children who experienced the event just one time. Further, the longer delay reduced accuracy only for consistent suggestions. Source-monitoring ability was strongly and positively related to resistance to suggestions, and encouraging children to identify the source of false suggestions allowed them to retract a significant proportion of their reports of inconsistent, but not consistent, suggestions. The results suggest that the gist consistency of suggestions determines whether event repetition increases or decreases suggestibility.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 | 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".