JOURNAL ARTICLE
Das Hienrecht – ein unbekannter Begriff der mittelalterlichen Rechtssprache.
Published In: Zeitschrift der Savigny-Stiftung fur Rechtsgeschichte: Germanistische Abteilung, 2023, v. 140, n. 1. P. 397 1 of 3
Database: Legal Source 2 of 3
Authored By: Deter, Gerhard 3 of 3
Abstract
The legal term "Hienrecht" corresponds legally to one law of living in bondage, which was widespread in north-western Germany in the Middle Ages. It has not been considered by legal history. The Hien (bondsmen) were – according to the etymological findings – members of the same household: some kind of tenants, then also the serfs of a grange. In Westphalia, the dependent farming population can be roughly divided into Hofhörige (corresponds approximately bondsmen), Eigenbehörige (some kind of serfdom) and members ofthe household/inmates. Hienrecht had its place within the framework of these different orders. On the one hand, the term Hien was associated with a certain form of serfdom, but on the other hand it could also refer to the persons in charge of the property. The Hienrecht described a specific legal and property form of the Unterhof of a villication, namely that of the Liten. In the late Middle Ages Hienrecht meant one of the legal relationships of bondage, then to be found in Westphalia, in particular probably that of Eigenbehörigkeit. Hienrecht referred to the sub-ownership of the rural tenants equipped with secured inheritance rights, which were composed in a Villication or a modified form of the same cooperative. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Zeitschrift der Savigny-Stiftung fur Rechtsgeschichte: Germanistische Abteilung. 2023/06, Vol. 140, Issue 1, p397
- Document Type:Article
- Subject Area:History
- Publication Date:2023
- ISSN:03234045
- DOI:10.1515/zrgg-2023-0010
- Accession Number:164627970
- Copyright Statement:Copyright of Zeitschrift der Savigny-Stiftung fur Rechtsgeschichte: Germanistische Abteilung is the property of De Gruyter 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.)
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