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Record W2789900073 · doi:10.25073/2588-1167/vnuls.4140

Improving the Mechanism to Examine Judgment Debtor’s Ability to Satisfy Civil Judgments in Vietnam from International Experience

2018· article· en· W2789900073 on OpenAlexaboutno aff
Nguyen Thi Bich Thao, Nguyễn Thị Hương Giang

Bibliographic record

VenueVNU Journal of Science Legal Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsDebtorEnforcementSanctionsCivil procedurePolitical scienceLawCommissionBusinessCreditorDebtFinance

Abstract

fetched live from OpenAlex

This article provides an overview of current law and current state of examining conditions of civil judgment enforcement in Vietnam and points out that the main shortcomings are the lack of a court’s supporting mechanism and lack of strict sanctions imposed on judgment debtors and other agencies, organizations and individuals who fail to provide information on the judgment debtor’s assets. The article explores the mechanism for examining of conditions for civil judgment enforcement in several countries such as the United States, the United Kingdom, and Canada and draws some experience for improving the law on examining conditions of civil judgment enforcement in Vietnam. Keywords Civil judgment enforcement, examining judgment debtor’s ability to satisfy civil judgment enforcement References [1] Council of Europe. 2003, “Recommendation Rec(2003)17 of the Committee of Ministers to Member States on Enforcement.” September 9, https://wcd.coe.int/wcd/ViewDoc.jsp?id=65531&Site=COE. [2] Henderson, Keith, Angana Shah, Sandra Elena & Violaine Autheman. 2004. “Regional Best Practices: Enforcement of Court Judgments. Lessons Learned from Latin America.” IFES Rule of Law White Paper Series, International Foundation for Electoral Systems, Washington, DC. [3] Hoàng Thị Thu Trang, Hoàn thiện quy định pháp luật về xác minh điều kiện THADS, Tham luận của Cục THADS tỉnh Nghệ An, http://thads.moj.gov.vn/nghean/noidung/tintuc/lists/nghiencuutraodoi/view_detail.aspx?itemid=13.[4] European Commission for the efficiency of justice, CEPEJ Guidelines for a better implementation of the existing Council of Europe's recommendation on enforcement, https://www.coe.int/t/dghl/cooperation/cepej/textes/Guidelines_en.pdf[5] Wendy A. Kennett, Enforcement of Judgments in Europe, Oxford University Press, 2000.[6] German Civil Procedure Code, https://www.gesetze-im-internet.de/englisch_zpo/englisch_zpo.html.[7] Federal Rules of Civil Procedure, http://www.uscourts.gov/rules-policies/current-rules-practice-procedure/federal-rules-civil-procedure.[8] California Civil Procedure Code, http://leginfo.legislature.ca.gov/faces/codesTOCSelected.xhtml?tocCode=ccp[9] Procedure for enforcing a judgment: England and Wales, https://e-justice.europa.eu/content_procedures_for_enforcing_a_judgment-52-ew-en.do?member=1[10] British Columbia Law Institute, Report on the Uniform Civil Enforcement of Money Judgment Acts, 2005.[11] Học viện Tư pháp, Giáo trình Nghiệp vụ thi hành án dân sự (Phần Kỹ năng), Tập 1, NXB. Tư pháp, 2017.

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)0.019
metaresearch head score (Gemma)0.032
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.050
GPT teacher head0.372
Teacher spread0.323 · 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
Published2018
Admission routes1
Has abstractyes

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