Bilingual and Multilingual Legal Dictionaries: New Standards for the Future
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Alarmed by the notorious inaccuracy of “traditional” bilingual and multilingual legal dictionaries, legal lexicographers began experimenting with new methods of improving user reliability about 15 years ago. Analyzing numerous bilingual and multilingual legal dictionaries of various languages (combinations of English, French, German, Spanish, Italian, Dutch and Chinese), the author claims that one can now speak of a special methodology of legal lexicography which has set new standards for the future. Focusing on the problems of interlingual transfer in the field of law, the author deals with the problem of equivalence, pointing out that, in the majority of cases, the functional equivalents of different legal systems are only partially equivalent. This has led to the need to measure the degree of their equivalence in order to determine their acceptability in dictionary entries. For this purpose, methods of comparative conceptual analysis can be used. Moreover, bilingual legal dictionaries are now equipped with a more or less elaborate documentary apparatus including definitions of both the source term and its equivalent, contextual data and geographic information on the usage of target language variants. In conclusion, the question is raised as to the role of dictionaries in the standardization of legal terminology at the national level (Canada), the regional level (EEC, CMEA) and at the international level (UN).
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it