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Record W3158348143 · doi:10.1111/gove.12594

Institutional proximity and judicial corruption: A spatial approach

2021· article· en· W3158348143 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

VenueGovernance · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversity of TorontoMcGill University
Fundersnot available
KeywordsOperationalizationPoliticsLanguage changeContext (archaeology)Political scienceChinaComplement (music)Law and economicsLawSociologyGeography

Abstract

fetched live from OpenAlex

Abstract This article develops a relational explanation for judicial corruption, namely, a spatial theory of institutional proximity, to complement existing behavioral and institutional approaches. Institutional proximity refers to the spatial proximity between adjacent political or social institutions, including courts. This proximity can be a result of political or administrative regulations, workplace interactions, or the mobility of individual actors between them. Linking ecologies and space travelers are two key spatial mechanisms through which institutional proximity enables judicial corruption. They pave the pathways of judicial corruption, that is, how corrupt transactions and related social interactions are facilitated by and communicated through institutions adjacent to the court. The theory is operationalized in the context of Chinese courts and the various pathways of judicial corruption are exemplified through a number of publicly reported cases in China.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.266
Teacher spread0.238 · 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