Young children’s understanding that promising guarantees performance: The effects of age and maltreatment.
Bibliographic record
Abstract
Two studies, with 102 nonmaltreated 3- to 6-year-old children and 96 maltreated 4- to 7-year-old children, examined children's understanding of the relative strengths of "I promise," "I will," "I might," and "I won't," to determine the most age-appropriate means of eliciting a promise to tell the truth from child witnesses. Children played a game in which they chose which of 2 boxes would contain a toy after hearing story characters make conflicting statements about their intent to place a toy in each box (e.g., one character said "I will put a toy in my box" and the other character said "I might put a toy in my box"). Children understood "will" at a younger age than "promise." Nonmaltreated children understood that "will" is stronger than "might" by 3 years of age and that "promise" is stronger than "might" by 4 years of age. The youngest nonmaltreated children preferred "will" to "promise," whereas the oldest nonmaltreated children preferred "promise" to "will." Maltreated children exhibited a similar pattern of performance, but with delayed understanding that could be attributed to delays in vocabulary. The results support a modified oath for children: "Do you promise that you will tell the truth?".
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".