The Influence of Defendant Immigration Status, Country of Origin, and Ethnicity on Juror Decisions
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
This study examined prejudicial attitudes toward immigrant defendants who vary on legal status, country of origin, and ethnicity. Three hundred twenty mock juror participants read a trial transcript that varied defendants’ immigration status (documented or undocumented), defendant country of origin (Canada or Mexico), and defendant race/ethnicity (Caucasian or Latino). Dependent measures included verdict, sentencing, culpability ratings, and trait assessments. European American mock jurors found undocumented, Latino immigrants from Mexico guilty significantly more often, more culpable, and rated this defendant more negatively on various trait measures in comparison with all other conditions. Latino mock jurors did not demonstrate ingroup favoritism or outgroup bias. This study examines aversive racism as a factor of this bias. Limitations and future directions 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.
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 | 0.004 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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