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Record W4407276660 · doi:10.54254/2753-7048/2024.20782

The Path of Constructing the Supported Decision-Making System in the Interaction Between International and Domestic Law

2025· article· en· W4407276660 on OpenAlexaboutno aff

Bibliographic record

VenueLecture Notes in Education Psychology and Public Media · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Political and Economic Relations
Canadian institutionsnot available
Fundersnot available
KeywordsPath (computing)LawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This article focuses on the path of constructing the supported decision-making (SDM) system in the interaction between international and domestic law, exploring the role of Article 12 of the Convention on the Rights of Persons with Disabilities (CRPD) in promoting this system globally. The article reviews the theoretical foundation of the supported decision-making system and analyzes the legislative practices in countries such as Germany, Japan, and Canada. It summarizes the interactive model where international law, through soft norms and supervision mechanisms, promotes domestic legal reforms. Article 12 of the CRPD, centered on “equal legal capacity” and “assistance and support,” provides guidance for contracting states in system innovation, advancing legislation through concluding observations and compliance monitoring, and promoting the transformation from the traditional guardianship system to the supported decision-making system. This article argues that the promotion of the supported decision-making system not only reflects international law’s guiding role in domestic law but also demonstrates how domestic practices feedback into and enrich the content of international law. This bidirectional interaction mechanism has laid a solid foundation for achieving the global goal of protecting the rights of persons with disabilities, providing both theoretical justification and practical support for the expansion of the supported decision-making system into other areas of rights protection.

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)0.001
metaresearch head score (Gemma)0.003
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.019
GPT teacher head0.382
Teacher spread0.362 · 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.

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
Published2025
Admission routes1
Has abstractyes

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