Prosocial lie-telling in preschoolers: The impacts of ethnic background, parental factors, and perceived consequence for the partner
Bibliographic record
Abstract
= 45). Children completed an online experiment involving two real-life politeness situations. In the first situation, children were asked whether they thought someone with a red mark on their face looked okay for a photo or a Zoom party (Reverse Rouge Task). In the second situation, upon hearing the researcher's misconception about two pieces of artwork, children were asked whether they agreed with the researcher (Art Rating Task). Parents completed questionnaires that measured their levels of collectivist orientation and parenting styles. Contrary to our hypotheses, the likelihood of children telling a prosocial lie did not vary as a function of their ethnic group or the presence of a perceived consequence for the partner, nor was it predicated by parental collectivist orientation. Interestingly, prosocial liars were more likely to have authoritative parents, whereas blunt-truth tellers were more likely to have permissive parents. These findings have important implications for the ways in which certain parenting styles influence the socialization of positive politeness in children. In addition, the similar rates of prosocial lying across the two ethnic groups suggest that children who are born and raised in Canada may be much more alike than different in their prosocial lie-telling behavior, despite coming from different ethnic backgrounds.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".