Legal Decisions of Preadolescent and Adolescent Defendants: Predictors of Confessions, Pleas, Communication with Attorneys, and Appeals.
Bibliographic record
Abstract
While there is an increasing recognition that developmental differences may exist in legal decision-making, little research has examined this. This study examined the legal judgments of 152 defendants aged 11-17 (73 females, 79 males). Adolescents aged 15 and younger were more likely than older adolescents to confess and waive their right to counsel, and less likely to report that they would appeal their case or discuss disagreements with their attorneys. Also, while adolescents aged 15-17 were more likely to confess, plead guilty, and accept a plea bargain if they perceived that there was strong evidence against them, younger defendants' legal decisions were not predicted by the strength of evidence. Importantly, defendants with poor legal abilities were more likely to waive legal protections, such as the right to counsel and to appeal. Defendants from below-average socioeconomic backgrounds were more likely to waive their interrogation rights, and defendants from ethnic minority groups were less likely to report that they would disclose information to their attorneys. The advice of attorneys, parents, and peers emerged as important predictors of plea decisions. None of the defendants reported that their parents advised them to assert the right to silence during police interrogation.
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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 | 0.001 | 0.015 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".