Promising to tell the truth makes 8‐ to 16‐year‐olds more honest
Bibliographic record
Abstract
Techniques commonly used to increase truth-telling in most North American jurisdiction courts include requiring witnesses to discuss the morality of truth- and lie-telling and to promise to tell the truth prior to testifying. While promising to tell the truth successfully decreases younger children's lie-telling, the influence of discussing the morality of honesty and promising to tell the truth on adolescents' statements has remained unexamined. In Experiment 1, 108 youngsters, aged 8-16 years, were left alone in the room and asked not to peek at the answers to a test. The majority of participants peeked at the test answers and then lied about their transgression. More importantly, participants were eight times more likely to change their response from a lie to the truth after promising to tell the truth. Experiment 2 confirmed that the results of Experiment 1 were not solely due to repeated questioning or the moral discussion of truth- and lie-telling. These results suggest that, while promising to tell the truth influences the truth-telling behaviors of adolescents, a moral discussion of truth and lies does not. Legal implications are discussed.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.006 | 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".