Bibliographic record
Abstract
The National Mobility Agreement 2013, a praiseworthy initiative of the Federation of Law Societies of Canada, will come into force following implementation by each law society. In the words of the Federation, this agreement “will extend the mobility provisions to permit Canadian lawyers to transfer between Quebec and the common law provinces with ease regardless of whether they are trained in Canadian common law or civil law.” To give full effect to this initiative, a basic understanding of Canada’s legal diversity is arguably required. In order to determine the importance placed by Canadian law schools on courses emphasizing Canada’s legal diversity, the relevant course content of twenty law schools during the 2011-12 and 2012-13 academic years was surveyed. The objective was to identify optional and compulsory courses relating to: a) Aboriginal law; b) Introduction to Canadian common law and Quebec civil law, offered in the context of stand-alone or comparative law courses; c) Statutory interpretation, specifically the interpretation of bilingual statutes and of bijural or harmonized federal legislation. The survey reveals that there are major gaps in this regard and that this could affect the competence of law graduates. Part 1 of the article spotlights the targeted courses available during the survey period. In Part 2, the author comments on the survey results and describes how law schools could easily incorporate course content that takes into consideration Canada’s diversified legal environment. In the event that law schools fail to act, the Federation should take the initiative since national mobility and knowledge of other legal systems, including knowledge of Canada’s common law and civil law systems, go hand in hand. The Federation cannot foster the one and ignore the other,particularly given the duty of all lawyers to be competent in the tasks that they undertake.
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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.066 | 0.009 |
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".