Distributive Justice for Others, Collective Angst, and Support for Exclusion of Immigrants
Bibliographic record
Abstract
Harsh treatment of others can reflect an underlying motivation to view the world as fair and just and also a dispositional tendency to believe in justice. However, there is a critical need to refine and expand existing knowledge, not only to identify underlying psychological processes but also to better understand how justice may be implicated in support for exclusionary policies. Across two studies, we show that support for policies that restrict immigrants is exclusively associated with thoughts about fair outcomes for other people (distributive justice for others). In Study 1, A mericans' dispositional tendency to believe in distributive justice for others was associated with greater support for a policy proposing to further restrict immigrant job seekers' capacity to gain employment in the U nited S tates. In Study 2, we experimentally primed thoughts about justice in a sample of U.S . police officers. Support for a policy that mandated stricter policing of illegal immigration was strongest among officers who first thought about fair outcomes for other people, relative to other unique justice primes. Across both studies, distributive justice for others was associated with greater collective angst —perceived threat towards the future existence of A mericans. Moreover, collective angst mediated the link between distributive justice for others and support for restrictive policies. Overall, this research suggests that thoughts about distributive justice for others can especially diminish compassion towards immigrants and other underprivileged groups via support for exclusionary policies. In addition, merely thinking about distributive justice for others may be sufficient to amplify social callousness.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".