MétaCan
Menu
Back to cohort
Record W3121780508 · doi:10.1086/698435

The Legal Academy’s Ideological Uniformity

2018· article· en· W3121780508 on OpenAlex
Adam Bonica, Adam Chilton, Kyle Rozema, Maya Sen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Journal of Legal Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
FundersUniversity at BuffaloUniversity of Illinois at Urbana-ChampaignLoyola Marymount UniversityWestern New England UniversityUniversity of ConnecticutCity University of New YorkWake Forest UniversityLoyola University ChicagoGeorgetown UniversityUniversity of DenverState University of New YorkUniversity of MinnesotaWashington University in St. LouisBoston CollegeHarvard UniversityUniversity of MiamiYork UniversityNorthwestern UniversityUniversity of WashingtonNorthern Illinois UniversityWashington and Lee UniversityUniversity of the PacificUniversity of Southern CaliforniaSanta Clara UniversityYale University
KeywordsIdeologyLawLegal professionDirectoryPoliticsPolitical scienceBalance (ability)SociologyPsychologyComputer science

Abstract

fetched live from OpenAlex

We study the ideological balance of the legal academy and compare it with the ideology of the legal profession more broadly. To do so, we match professors listed in the Association of American Law Schools’ Directory of Law Teachers and lawyers listed in the Martindale-Hubbell directory to a measure of political ideology based on political donations. We find that 15 percent of law professors, compared with 35 percent of lawyers, are conservative. This may not simply be due to differences in their backgrounds: the legal academy is still 11 percentage points more liberal than the legal profession after controlling for several relevant individual characteristics. We argue that law professors’ ideological uniformity marginalizes them but that it may not be possible to improve the ideological balance of the legal academy without sacrificing other values.

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.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.821
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.130
GPT teacher head0.464
Teacher spread0.334 · 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