MétaCan
Menu
Back to cohort

Legal Mobilization on the Terrain of the State: Creating a Field of Immigrant Rights Lawyering in France and the United States

2011· article· en· W841711676 on OpenAlexfundno aff
Leila Kawar

Bibliographic record

VenueLaw & Social Inquiry · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsnot available
FundersUniversity of CambridgeYork UniversityHarvard UniversityU.S. Department of Justice
KeywordsPolitical scienceState (computer science)Social movementImmigrationLawPoliticsScholarshipInstitutionalisationSociology

Abstract

fetched live from OpenAlex

Scholarship on law and social movements has focused attention primarily on the United States, and secondarily on countries that share the Anglo‐American legal tradition. The politics of law and social movements in other national legal contexts remains underexamined. The analysis in this article contrasts legal mobilizations for immigrant rights in France and the United States, and explores the relations between national fields of power and legal practices. I trace the institutionalization of immigrant rights legal organizations in each country and argue that the divergent organizational forms and litigation strategies adopted by professionalized movement organizations reflect the dynamics of the nationally distinct fields of power relations within which law reform has been conducted. My analysis links the material and symbolic resources available to law reformers to the relative authority of private and public juridical actors in each state.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0300.026
Scholarly communication0.0140.005
Open science0.0010.010
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.239
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations58
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueLaw & Social InquirySame topicHistorical and Contemporary Political DynamicsFrench-language works237,207