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Record W4403741011 · doi:10.5539/jpl.v17n4p30

A Comparative Analysis of the Right of Recourse between Co-Guarantors

2024· article· en· W4403741011 on OpenAlexvenueno aff
Rongxin Zeng

Bibliographic record

VenueJournal of Politics and Law · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Environmental Law and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsBusinessMathematical economics

Abstract

fetched live from OpenAlex

This paper examines a crucial aspect of the legal framework governing the rights of recourse between co-guarantors. It focus on the Chinese context while drawing insightful comparisons with France, Germany, and the United States. A comprehensive analysis of the pertinent provisions of the Civil Code of the People's Republic of China and the Supreme People's Court interpretations reveals inconsistencies and ambiguities that necessitate further examination. To enhance the discourse, the paper contrasts Chinese regulations with those of France, Germany, and the United States, elucidating disparate approaches and potential best practices. This comparative analysis not only identifies the strengths and weaknesses of China's current stance but also suggests avenues for improvement. By examining foreign legal systems, the study identifies areas where Chinese law could be refined to better align with international standards and principles of fairness. The findings emphasize the necessity for the establishment of a more coherent and equitable legal framework in China, one that provides clear and unambiguous guidelines for co-guarantors seeking recourse. It is recommended that steps be taken to address the discrepancies identified and to advocate for reforms that promote legal clarity and enhance the protection of co-guarantors' rights. The paper concludes with a recommendation for comprehensive legislative reform, emphasizing the importance of balancing the interests of all parties involved in co-guarantee arrangements in order to foster a more robust and internationally compatible legal environment.

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)0.007
metaresearch head score (Gemma)0.011
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: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.011
Scholarly communication0.0040.005
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.000

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 head0.013
GPT teacher head0.289
Teacher spread0.277 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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