Bibliographic record
Abstract
In this article, the author examines three visions of the future of law schools. The first vision is that they should focus on producing "practice ready lawyers" to meet the immediate needs of today's legal profession. The second is that law schools should focus on training "tomorrow's lawyers, "graduates who are able to adapt to a rapidly-changing world. The third insists that law schools are knowledge communities whose many functions include, but are not limited to, providing students with a large and liberal understanding of law that will prepare them for a variety of legal and non-legal careers and for participation as citizens in the broader economy and polity. Although the future of law schools is contested and uncertain, the author predicts, law schools will be celebrated in the long term for their distinguished scholarship, their contributions to the public good, and their role as agents of change rather than for skills training, their influence on day-to-day legal practice, and their purveying of conventional wisdom.
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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.015 | 0.030 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".