Adult’s veracity judgments of Black and White children’s statements: the role of perceiver and target race and prejudice-related concerns
Bibliographic record
Abstract
Introduction: Seldom has work investigated systematic biases in adults' truth and lie judgments of children's reports. Research demonstrates that adults tend to exhibit a bias toward believing a child is telling the truth, but it is unknown whether this truth bias applies equally to all children. Given the pervasiveness of racial prejudice and anti-Black racism in the United States, the current study examined whether adults are more or less likely to believe a child is telling the truth based on the race of the child (Black or White), the race of the adult perceiver (Black or White), and the perceiver's concerns regarding appearing unprejudiced. Methods: Using an online data-collection platform, 593 Black and White American adults reviewed fictitious vignettes in which a child denied committing a misbehavior at school (e.g., damaging a laptop). The race of the child in the vignette was manipulated using an AI-generated photo of either a Black child or a White child. After reading each story, participants provided a categorical veracity judgment by indicating whether they believed the child in the story was lying (and therefore committed the misdeed) or telling the truth (and was innocent), as well as rated how honest or deceptive the child was being on a continuous scale. Participants also completed questionnaires assessing their internal (personal) and external (normative) motivations to respond in non-prejudiced ways. Results and discussion: Results indicated that systematic racial biases occur in adults' veracity judgments of children's statements. Both Black and White participants exhibited a truth bias in their veracity judgments of Black children, but not when evaluating the deceptiveness of White children. Consistent with the prejudice-related concerns hypothesis, the observed truth bias toward Black children was moderated by individual differences in participants' desire to respond without prejudice and whether those motivations stem from external or internal sources. The current findings present novel evidence regarding racial bias and prejudice-related concerns as potential barriers to making veracity judgments of children's statements and, ultimately, successful lie detection.
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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".