Legal system: an additional variable in the analysis of short-term diachronic evolution of legal terminology
Bibliographic record
Abstract
Abstract The inclusion of specialised corpora in terminological studies since the early 1990s has allowed for the observation and description of the behaviour of terminology in authentic linguistic contexts. As a result, what is nowadays known as “Textual Terminology” (Bourigault & Slodzian 1999, Pour une terminologie textuelle. Terminologies Nouvelles 19. 29–32) has become commonplace practice in the study of terminology. This new approach to terminology has led to the development of alternative paradigms to the General Theory of Terminology and to increasing interest in terminological variation, i.e. the existence of multiple terms to refer to a single concept. In this paper, the focus is on terminological variation in legal terminology. Variation in terminology can be studied from a number of perspectives and the one undertaken here is diachronic. The aim of the paper is to determine whether legal terminology, being “the most visible and striking linguistic feature of legal language” (Cao 2007: 53, Translating law . Clevedon/Buffalo/Toronto: Multilingual Matters) but also deemed to change very slowly (Lemmens 2011, The slow dynamics of legal language: Festina lente? Terminology 17(1). 74–93), is subject to terminological variation in the short term and, if so, what type of variation it experiences. To do so, European Union legal acts in English and Italian and national legal acts in Italian dealing with the topic of victims of crime and their rights were examined and concrete examples of denominative and conceptual variation were extracted. The presence of two legal systems in the analysis made it necessary to add the ‘legal system’ variable to the methodological framework to provide a more comprehensive picture of the types of short-term variation detected. The inclusion of this variable led to the classification of the variants into two types, i.e. ‘intra-systemic’ and ‘inter-systemic’ variation. Moreover, an attempt was also made to classify the variants discussed in the paper against Picton’s typology for the description of short-term knowledge evolution through terminology (Picton 2014, The dynamics of terminology in short-term diachrony. A proposal for a corpus-based methodology to observe knowledge evolution. In R. Temmerman & M. Van Campenhoudt (eds.), Dynamics and terminology. An interdisciplinary perspective on monolingual and multilingual culture-bound communication , 157–182. Amsterdam & Philadelphia: John Benjamins). This attempt resulted in the recognition of the lack of suitable categories for all the types of variation identified and thus of the need for further investigation of the dynamics of legal terminology embedded in a multi-level jurisdiction such as the EU.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".