Legal Education and Training Review: a five-year retro/prospective
Bibliographic record
Abstract
The Legal Education and Training Review final report on the regulation of legal services education and training was published in June 2013. Five years later, members of the research team reflect, in this article, on subsequent developments in the relationship between regulator and regulated. They explore the links between outcomes-focused regulation (OFR) and the hierarchies within the regulatory space and between the OFR-driven focus on competence and its impacts on assessment for qualification and continuing competence thereafter. Finally, they extend the concept of shared space to include the relationship between regulators who commission research and researchers who carry it out. The paper concludes that the project has attracted international interest and informed other projects. Although there is already clear impact in England and Wales, the full significance of the report in the canon of seminal reports into legal education will emerge over the next decade.
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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 | 0.110 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.024 | 0.016 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".