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Record W2144842435

Contract Law is Not Enough: The Many Legal Institutions That Support Contractual Commitments

2004· article· en· W2144842435 on OpenAlexaff
Gillian K. Hadfield

Bibliographic record

VenueSSRN Electronic Journal · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnforcementLawmakingTransaction costBusinessContract managementLaw and economicsDatabase transactionWork (physics)StructuringLawEconomicsPolitical scienceFinanceLegislature
DOInot available

Abstract

fetched live from OpenAlex

One of the fundamental contributions of transaction cost theory and institutional economics has been to focus attention on opening the "black box" of contract enforcement, drawing attention to the institutions required to achieve effective and low-cost contract enforcement. The idea that the effectiveness of contract law is critical to the growth of economic activity is widespread in the literature on development and transition economies. Recent studies attempting to document toe relative strength of contract enforcement in different settings (La Porta, et al., 19982; Djankov, et al., 2003), however, have focused on relatively abstract notions of "courts" and "legal systems" and have yet to investigate the detailed institutional features that make contract law effective and low-cost. Even if it is correct to identify "common law legal systems" as productive of greater economic growth, for example, we still do not know what it is about those systems that produces this growth and in particular how these systems achieve more effective and lower cost contract enforcement. This paper explores in a detailed way the multiple legal institutions at work in the organization of courts, the judiciary, the legal profession, enforcement services, and the process of lawmaking and legal innovation, all of which play significant roles in structuring an effective and cost-effective regime of contract enforcement.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.240
Teacher spread0.204 · 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.

Study designTheoretical or conceptual
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

Citations6
Published2004
Admission routes1
Has abstractyes

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