Bibliographic record
Abstract
This article discusses some of the costs and benefits of multilingual legislation, focusing largely on Canada and the European Union. Courts interpreting these laws must take into account the different language versions, since each version is equally authoritative. Fidelity to the legislature’s will comes with very high stakes in this context, because multilingual legislative systems are most typically a means for recognizing the autonomy of minority groups, which, in exchange, cede some of that autonomy to a higher legal order. Thus, there is a special moral duty to ensure that the laws are construed faithfully at the same time that language barriers make it appear, at least on the surface, that it is more difficult to do so. Moreover, the risk of judges substituting their own values for those of the legislature when there is no single, definitive legal text, appears to become magnified in multilingual settings, creating the risk of decision making that would not stand up to moral scrutiny even in monolingual systems. This article argues that despite the apparent difficulties inherent in multilingual legislation, it actually reduces uncertainty in meaning by creating additional data points for statutory interpreters to consider. Multilingualism does, however, lead to certain additional problems of ambiguity. These, for the most part, however, are generally resolved fairly easily. It is further argued that the European approach to interpretation, which I call Augustinian Interpretation, is likely to lead to results more faithful to the legislature’s intent than is the standard Canadian approach, called the Shared Meaning Rule. Arguments from case law, from linguistics and from the philosophy of language are adduced to support these conclusions.
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.
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 | 0.027 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.090 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".