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Law, Empires, Legal Professions, and Status Hierarchies: Comparative Perspectives

2025· article· en· W4411599541 on OpenAlexaffabout
Ronit Dinovitzer, Bryant G. Garth

Bibliographic record

VenueAnnual Review of Law and Social Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLegal statusEmpirical legal studiesPolitical scienceLawLegal pluralismLegal professionLaw and economicsLegal realismSociology

Abstract

fetched live from OpenAlex

This article examines the local and global processes that produce and shape the legal profession and its relevant national hierarchies, emphasizing the role of law schools, practice settings, career pathways, legacies of imperialism, colonialism, and external forces such as globalization. Focusing on Canada, India, South Korea, and Brazil, the article explores how global forces like Americanization and neoliberalism intersect with national histories and legal traditions. It traces the rise of corporate law firms, their influence on legal education, and the persistent disparities between elite and nonelite institutions. Case studies reveal the complex interconnections between traditional family-based hierarchies, meritocratic credentials, and evolving professional norms. Despite pressures for reform, entrenched structures often absorb changes, reinforcing local and global status hierarchies. This work underscores the enduring tension between merit and inherited privilege in the legal field, the power of interconnected histories, and their implications for the role and status of legal professions.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.008
Science and technology studies0.0060.027
Scholarly communication0.0080.007
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.046
GPT teacher head0.474
Teacher spread0.428 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes2
Has abstractyes

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