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Record W2121670655 · doi:10.1002/bsl.517

The verdict on jury trials for juveniles: the effects of defendant's age on trial outcomes

2003· article· en· W2121670655 on OpenAlexaff
Diane Louise Warling, Michele Peterson‐Badali

Bibliographic record

VenueBehavioral Sciences & the Law · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsVerdictJuryPsychologyEconomic JusticeJury trialSocial psychologySample (material)CriminologyLawPolitical science

Abstract

fetched live from OpenAlex

With the progression to more adult-like policies and procedures for youth in the justice system, the right to a jury trial has been extended to young offenders. These youth would not be tried by a jury of their peers, however, but by a jury of adults. The concern is that adult jurors may hold negative attitudes about youth that might influence their decision making in a case involving a young defendant. Two studies examined whether and under what conditions defendant's age affects jurors' decisions about the guilt and sentencing of an accused. In study 1, data were gathered from two samples of jury eligible adults: one university sample and one public sample. Mock jurors read written transcripts of a trial involving a defendant who was presented as either 13, 17, or 25 years of age. Results indicated that the defendant's age had no effect on mock jurors' verdict or their ratings of defendant guilt. However, younger defendants were granted shorter sentences than the adult defendants. In study 2, mock jurors read the same trial presented in study 1 but were asked to deliberate about the case and render group verdicts. These group verdicts did not differ significantly by defendant's age. Age-related themes that emerged from group deliberations were identified, and results indicated that age tended to be used as a mitigating factor in favor of youth rather than against them. These findings are discussed in terms of their implications for youth justice policy and practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0040.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.162
GPT teacher head0.444
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations52
Published2003
Admission routes1
Has abstractyes

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