The Effects of Perceived Threat, Political Orientation, and Framing on Public Reactions to Punitive Immigration Law Enforcement Practices
Bibliographic record
Abstract
This study explores variation in people’s reactions to a punitive immigration law enforcement practice. Using a vignette-styled framing-effects experiment, we examined whether reactions to the practice depend, in part, on who receives its consequences. More than 500 undergraduates from a large Mid-Atlantic university read a brief vignette about an immigrant motorist who is stopped by a police officer for a broken taillight violation and then detained for failing to document his legal immigration status. We manipulated three characteristics of the motorist in the vignette, including his nationality (Mexico/Canada), occupation (factory worker/software engineer), and documentation status (documented/undocumented). When we framed the motorist as an unauthorized immigrant, the subjects were more likely to condone the officer’s intrusive actions. We also found that the subjects’ political orientation and immigrant threat perceptions were powerful predictors of their normative reactions to the vignette.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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".