Juror motivations: applying procedural justice theory to juror decision making
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Jurors sometimes consider inadmissible evidence in their verdicts, despite judicial instructions to disregard that evidence. Procedural justice research suggests this is because jurors are motivated to prioritise just outcomes over due process; thus, jurors’ non-compliance towards judicial instructions to disregard inadmissible evidence may be the product of a discrepancy between legal and lay peoples’ understanding of the juror’s role. In this mixed-method design, we examined 294 university students’ a priori perceptions about the role and responsibility of jurors, and empirically tested how randomly assigning participants to the role of a juror (versus a judge’s associate/assistant, who helps the judge to ensure a trial is conducted according to proper procedure) influenced their verdict decisions, prioritisation of outcome versus procedural considerations, motivation to protect the community, and perceived obligation to ensure correct procedures. Overall, the results demonstrated ambivalence in lay people’s perceptions of the juror role, with many participants perceiving jurors to be responsible for protecting society; however, we did not find support for our predictions that participants assigned the role of a juror (versus judge’s associate) would more strongly prioritise outcomes over procedures. Methodological issues, recommendations for future research, and implications are also discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 it