Hollow law and utilitarian law: The devaluing of deportation hearings in New York City and Paris
Bibliographic record
Abstract
Abstract How is law made worthless to the marginalized? Drawing on ethnographic observations in Paris and New York City, I establish a typology of devaluation practices in deportation hearings. I analyze how informal court practices devalue court actors, the hearing, and the law itself. Despite different levels of formal protections for migrants, deportation adjudication is pared down and devalued in both cities. This devaluation, however, followed distinct logics. New York hearings were characterized by a utilitarian law logic, where process and ritualistic elements deemed inessential were shed, leaving a stripped-down core focused on case processing. The minimal protections available to migrants were weakened further. By contrast, hollow law emerged in Parisian hearings, where everyday court practices eroded the more generous protections granted to migrants through formal law. While analyses of immigration adjudication have focused on decision-making, determinants of legal outcomes, and the interpretation of formal criteria, I instead conceptualize the courtroom as a space where value is actively unmade through informal practices, drawing on insights from the sociology of valuation and evaluation.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".