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Record W4311165496 · doi:10.1257/jel.20201330

Legal Markets

2022· article· en· W4311165496 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Economic Literature · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicOccupational and Professional Licensing Regulation
Canadian institutionsSchwartz/Reisman Emergency Medicine Institute
Fundersnot available
KeywordsInvestment (military)GlobalizationEconomicsMarket economyChinaBusinessEconomic systemLawPolitical science

Abstract

fetched live from OpenAlex

The existence of an effective legal system is assumed throughout economic analysis, and yet there has been little study of the economics of legal markets themselves. Research to date has focused narrowly on the economics of markets for lawyers. In this review, I distinguish legal markets from the market for lawyers and show how excessive regulation of our legal markets—by lawyers themselves—distorts economic activity and growth. It does so primarily by inhibiting investment in the legal and regulatory technologies needed to respond to the transformation of the economy wrought by globalization, digitization, aspirations for inclusion, and the coming of artificial intelligence. (JEL J44, K00, K40, L84)

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.014
GPT teacher head0.227
Teacher spread0.212 · 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