System Justification and Normative Influence: Jury Decision-Making in a Police Shooting Trial
Bibliographic record
Abstract
This study investigated whether normative influence (i.e., arguments to conform to the group) was related to jurors' system justification (SJS) beliefs (i.e., beliefs that justify a racially disparaging societal status quo) and time pressure during the deliberation phase of a mock criminal trial.Given the traumatic colonial context that exists between Indigenous communities in Canada and the police, as well as the current disproportionalities of Indigenous people in the Canadian criminal justice system, jurors with lower SJS may be compelled to use normative influence to persuade other jurors to conform to their verdict preference for an Indigenous defendant who raised a claim of self-defence for the killing of a police officer.Further, past research has found a relation between time pressure and normative influence.Thus, lower SJS and time nearing the end of the deliberation were hypothesized to be related to greater normative discussion content.Deliberations were transcribed, coded, and analyzed for 11 mock juries (N = 83 jurors) in a simulated first-degree murder trial.Findings did not support a relationship between normative influence and either SJS or time.This research may bear implications for our understanding of jury decision-making processes and how to instruct jurors.This thesis was a product of two years' worth of scholarship, meaningful mentorship, and invaluable friendship to which I am deeply grateful.I must firstly express my sincerest appreciation to my supervisor and mentor, Dr. Evelyn Maeder: a trailblazer in her field who offered me her guidance, supported and enriched my ideas along the way, and never failed to make time for me despite all the people who depend on her every day.It is an understatement for me to say that you have inspired me and profoundly impacted my life.The gratitude I feel towards
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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 | 0.007 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".