The relation between 8- to 17-year-olds’ judgments of other’s honesty and their own past honest behaviors
Bibliographic record
Abstract
The present investigation examined whether school-aged children and adolescents’ own deceptive behavior of cheating and lying influenced their honesty judgments of their same-aged peers. Eighty 8- to 17-year-olds who had previously participated in a study examining cheating and lie-telling behaviors were invited to make honesty judgments of their peers’ denials of having peeked at the answers to a test. While participants’ accuracy rates for making honesty judgments were at chance levels, judgment biases were found based on participants own past cheating and lie-telling behaviors. Specifically, those who cheated and lied were biased towards believing that their peers would behave in the same manner. In contrast, participants who had not cheated were biased towards judging their peers as honest. These findings suggest that by 8 years of age there is a relation between one’s own deceptive behaviors and judgments of other’s honesty.
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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 | 0.001 | 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 | 0.000 |
| 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".