"A NEED FOR A NEW KIND OF LAWYERING" TO BE THE TOPIC OF ANNUAL SIBLEY LECTURE
Bibliographic record
Abstract
Monday, March 25, 2002 WRITER: Heidi Murphy, 706/542-5172, hmurphy@uga.edu CONTACT: Paul Kurtz, 706/542-7140, pmkurtz@uga.edu "A NEED FOR A NEW KIND OF LAWYERING" TO BE THE TOPIC OF ANNUAL SIBLEY LECTURE ATHENS, Ga. - Professor of Law Carrie Menkel-Meadow will address the provocative topic of "A Need for a New Kind of Lawyering" for the new century in her presentation of the 94th Sibley Lecture to be held on Monday, April 1 at 3:30 p.m. in the law school's Hatton Lovejoy Courtroom. The lecture is open to the public. Admission is free. According to Menkel-Meadow, in a modern world of multiple parties and multiple issues within most legal and social problems, the lawyer's role must expand to incorporate new roles as mediators, consensus builders, facilitators, meeting managers and problem solvers. Drawing on such wide ranging sources as political theory (democratic deliberation and participation), game theory, popular culture (John Nash and A Beautiful Mind), literature (Ian McEwen's Enduring Love) and examples from actual legal practice, she will illustrate her point. Menkel-Meadow is professor at Georgetown University Law Center where she also directs the Georgetown-Hewlett Program on Conflict Resolution and Problem Solving and chairs the Georgetown-CPR Commission on Ethics and Standards in Alternative Dispute Resolution. She has written extensively in the fields of dispute resolution, legal ethics, feminist theory, legal education and the sociology of the legal profession. In addition to her scholarship, teaching and training, Menkel-Meadow is an active mediator and arbitrator and has trained mediators and lawyers throughout the U.S., Europe, South America, Australia and Japan. Menkel-Meadow holds a B.A. magna cum laude from Barnard College, Columbia University, a J.D. cum laude from the University of Pennsylvania and an LL.D. (Hon.) from Quinnipiac College of Law. Before joining the Georgetown faculty, she taught at UCLA, the University of Pennsylvania, Stanford and the University of Toronto. She has also been a visiting professor at Harvard University and Temple University. The Sibley Lecture Series, established in 1964 by the Charles Loridans Foundation of Atlanta in tribute to the late John A. Sibley, is designed to attract outstanding legal scholars of national prominence to the UGA School of Law. Sibley was a 1911 graduate of the 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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.147 | 0.057 |
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".