El glossari de termes jurídics anglès-tàmil d'Ontario: un projecte socioterminològic apoderador
Bibliographic record
Abstract
EnglishIn this article, the idea of norm in language is compared to the notion of law in the application of justice, and how rules in both fields must be interpreted not in a rigid manner, but in a way that is appropriate to context. The case used to illustrate this principle of flexibility and adaptability is a community-based legal terminology and lexicography project developed with, by and for the Canadian-Tamil community of Ontario, Canada catalaEn aquest article, comparem la nocio de norma del camp de la linguistica amb la de llei en l’aplicacio de la justicia, i com les regles de tots dos ambits no han de ser interpretades d’una manera rigida sino adequada al context. El cas que utilitzem per il·lustrar aquest principi de flexibilitat i adaptabilitat es un projecte lexicografic i de terminologia juridica que s’ha dut a terme en el marc de la comunitat canadencotamil d’Ontario (Canada) i que s’ha desenvolupat amb la col·laboracio d’aquesta mateixa comunitat, la qual, a mes, es beneficiaria i autora del projecte.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".