Długo wyczekiwany podręcznik przekładu prawniczego: recenzja książki "Przekład prawny i sądowy" Anny Jopek-Bosiackiej
Bibliographic record
Abstract
Neglected for years by researchers, legal translation has recently observed a revival within Translation Studies all over the world.It is closely connected with the intensive development of research on specialised (LSP) translation and the growth of translatortraining institutions, fuelled by the increased demand on the translation market related to globalisation and the European Union.In the last decade three notable books, i.e.Ńarčević (1997), Alcaraz and Hughes (2002) and Cao (2007), were published; however, none of them is well-suited for training Polish legal translators.Ńarčević is theoretically oriented and focuses mainly on translation of legislation in multilingual countries (e.g.Canada) while practically-oriented Alcaraz & Hughes and Cao do not use Slavonic languages as their point of reference.Likewise, the Polish publication by Kierzkowska (2002) is not intended to be a textbook. Przekład. Mity i Rzeczywistość [Translation/Interpreting. Myths and Reality], a new series by the PWN publishing house, fills the market niche with its accessible books on audiovisual translation, community interpreting, conference interpreting, and, last but not least, legal translation.In particular, Jopek-Bosiacka's Przekład prawny i sądowy [Legal and Court Translation], published in Polish and dedicated specifically to Polish and English translation, meets the long-felt need.It is the first book, both comprehensive and succinct in its treatment of the subject, which surveys various branches of legal translation and is a convenient compilation and synthesis of knowledge scattered in various Polish and English sources.It is worth noting that the author is both a linguist and a lawyer and manages to integrate both perspectives in her writing.The book may be divided into two parts.The first discusses properties of English and Polish legal language within the discourse analysis methodology, while the second follows the genre-based approach to translation (cf.Alcaraz & Hughes 2002: 101) and surveys major legal genres.These include: contracts, company law documents, national
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".