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Record W3121370532

The Administrative Foundations of Self-Enforcing Constitutions

2008· article· en· W3121370532 on OpenAlexaff
Yadira González de Lara, Avner Greif, Saumitra Jha

Bibliographic record

VenueSSRN Electronic Journal · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsCanadian Institute for Advanced Research
Fundersnot available
KeywordsIncentiveAdministrative lawRule of lawLaw and economicsConstitutional lawPolitical sciencePublic lawPower (physics)LawEconomicsPoliticsMicroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Current theories of the rule of law argue that public officials respect rights if the citizens are coordinated on an equilibrium in which they collectively resist abuse. Constitutional rules are means to coordinate on this equilibrium. In past and present states, however, constitutional rules often have no effect on the rule of law. This paper suggests an alternative view of the origin and development of the rule of law. Instead of considering constitutional rules as coordination devices for citizens at large, history suggests considering them as manifestations of equilibria with rulers constrained by “administrators ” required to implement policy. Analysis of the administrative foundations of self-enforcing constitutions may be the key to a theory and policy that would foster the rule of law in developing countries and those in transition. In particular, constitutional reforms might benefit from focusing on altering the equilibrium distribution of administrative capacity and power, providing incentives to the administratively powerful to check predation by each other and the central authorities, and to align administrators ’ interests with social welfare.

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)0.010
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0050.026
Scholarly communication0.0090.007
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.037
GPT teacher head0.323
Teacher spread0.285 · 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 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

Citations5
Published2008
Admission routes1
Has abstractyes

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