Children's Ability to Estimate the Frequency of Single and Repeated Events
Bibliographic record
Abstract
Although it is extremely important when interviewing children about alleged abuse to determine whether the abuse was a single or a repeated occurrence, we have little information about how children judge the frequency of events. The aim of the current study was to examine children's accuracy in providing estimates of event frequency that were numerical (that is, 1, 2, 3, …) and qualitative (that is, once, a few times, or many times). Younger (4- to 5-year-old) and older (6- to 8-year-old) children took part in a single event or an event that was repeated 6 or 11 times. They were interviewed after a short or long delay; some were interviewed a second time. Overall, children were very accurate at judging the frequency of a single event, but much less so for repeated events. Based on our findings, we make two recommendations for professionals trying to establish the frequency of events when interviewing young children.
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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 | 0.005 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".