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Record W4386958666 · doi:10.1111/lasr.12665

Hollow law and utilitarian law: The devaluing of deportation hearings in New York City and Paris

2023· article· en· W4386958666 on OpenAlexfundno aff
Lili Dao

Bibliographic record

VenueLaw & Society Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDeportationAdjudicationDevaluationLawSociologyImmigration lawImmigrationPolitical scienceCurrencyCriminologyEconomics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.336
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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