JOURNAL ARTICLE
Index 2023.
Published In: Uniform Law Review, 2023, v. 28, n. 3/4. P. 534 1 of 2
Database: Legal Source 2 of 2
Abstract
The document titled "Index 2023" is a compilation of articles published in the Uniform Law Review. The articles cover a range of topics, including the enforcement of arbitral awards, digital assets and private law, exemption clauses, the reception of OHADA law in Anglophone Cameroon, the environmental impact of digital technology, algorithmic mistakes in machine-made contracts, the use of emerging technologies in commercial transactions, the influence of the Italian model of hardship in international trade, tackling cultural objects acquisition, access to justice for multinational corporations, credit instruments for global food insecurity, security rights in cryptoassets, transnational contracts, the metaverse in trademark law, reconciling smart contracts with general clauses, critical appraisal of provisions on anticipatory non-performance, transnational law and digital trade, alternative dispute resolution systems, forum selection agreements in international commercial contracts, the CISG in the digital economy, artificial intelligence in corporate governance, ethical considerations in OHADA arbitration, statutory freedom in simplified joint-stock companies, financial market regulation and private law, competing claims to cryptoassets, and cryptoassets and public offerings in the CEMAC region. The document also includes updates on international developments in the field of law. [Extracted from the article]
Additional Information
- Source:Uniform Law Review. 2023/12, Vol. 28, Issue 3/4, p534
- Document Type:Article
- Subject Area:Law
- Publication Date:2023
- ISSN:11243694
- DOI:10.1093/ulr/unae018
- Accession Number:178481016
- Copyright Statement:Copyright of Uniform Law Review is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.