The Urge to Enlarge the Nigerian Law School Curriculum: Queries From Without, Answers From Within
Bibliographic record
Abstract
Legal practitioners and legal educators are of the opinion that the Nigerian Law School Curriculum is archaic. They urge that the curriculum be reviewed to include new courses to bring it up to speed, make it amenable to best international practices, and make the new wigs ready for the legal services market. That is the query from without. Teachers and legal educators in the Nigerian Law School are of the view that the curriculum is adequate for the purpose of training twenty first Century lawyers. That is the answer from within. This chapter sets out to examine the current curriculum of the Nigerian Law School with a view to showing that it is adequate for training lawyers and that the call for expanding the curriculum to include new courses is unfounded. It compares, briefly, the situation in Nigeria with those in the England and Wales and Canada. Both doctrinal and empirical research methods are used in collating and analysing relevant primary and secondary legal data. The chapter concludes that all the aspects of the current curriculum are modern and good for purpose; that new lawyers get better, professionally, through continuing legal education. It recommends, inter alia, that participation in law clinics be made compulsory for all students of the Nigerian Law School.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".