Justice as Told by Judges: The Case of Litigation over Local Anti-Immigrant Legislation
Bibliographic record
Abstract
In the absence of comprehensive immigration reform at the federal level, many American states and localities are undertaking their own legal reforms. The new state and local laws have been challenged by immigrant-rights organizations and individuals on the grounds that the federal government has already pre-empted the field. The lawsuits bring a new narrative voice—that of judges—into the boiling U.S. immigration debate. Judges engage the controversy over local enforcement of immigration enforcement, as they have other contentious disputes, both as pragmatic decision-makers and as spokespersons for justice. The tensions this dual role entails are explored here in the context of a single, controversial case. Close-up analysis of the judge’s narrative strategy reveals a range of specific techniques to create moral distance from a decision, combined, ironically, with the enlistment of moral themes to justify the ruling. The inter-twining of rule-of-law and justice rhetoric mirrors and also shapes a broader politics of justice in the United States.
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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 | 0.020 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.070 | 0.032 |
| Scholarly communication | 0.025 | 0.010 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.033 | 0.026 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".