Bibliographic record
Abstract
This article covers three years of Transnational Legal Practice developments outside of the US. (It is the companion piece to 47 Int'l Law. 499 (2013) which discusses US developments.) This article discusses the approval of an Alternative Business Structure licensing system by the UK Solicitors Regulation Authority and its subsequent issuance of ABS licenses. The second section reviews the emergence of the “Troika” as a new regulatory influence in Europe, citing as an example the joint ABA-CCBE letter to the IMF. (The Troika refers to the International Monetary Fund, the European Central Bank, and the European Commission.) The third section of the article reviews global developments that involve liberalization or contraction in market access for foreign lawyers, highlighting developments in Singapore, Korea, Malaysia, Brazil and India. The next section provides information about the Asia Pacific Economic Cooperation (APEC) Legal Services Inventory, which is a new web-based resource. It also discusses the September 2012 first-ever International Conference of Legal Regulators. The final section of the article highlights selected transnational legal practice developments around the globe, including developments in Australia, Canada, the UK, and the EU, including developments related the application of anti-money laundering rules to the legal profession
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.041 | 0.006 |
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".