Perceptions of Police Use of Force: The Influence of Inconsistencies, Victim Race, Defendant Race, and Situation Type on Mock-Juror Decision-Making
Bibliographic record
Abstract
The current set of studies examined whether various factors influenced mock-juror decision-making for a use of force case with a police officer defendant. Study 1 examined the effect of the number of inconsistencies (3 vs. 9), victim race (White vs. Indigenous), and defendant race (White vs. Indigenous). Results showed that a higher number of inconsistencies and a White defendant elicited less favourable perceptions of the defendant and higher perceptions of guilt. Study 2 examined the effect of the type of emergency situation (mental health check vs. domestic violence), victim race (White vs. Indigenous), and defendant race (White vs. Indigenous). Results showed that a mental health check situation, an Indigenous victim, and a White defendant elicited less favourable perceptions of the defendant and higher perceptions of defendant guilt. Participant attitudes were also examined and found to be influential on decision-making. Implications of the findings and directions for future research are discussed.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".