An Introduction to David Wexler, the Person Behind Therapeutic Jurisprudence
Bibliographic record
Abstract
The author is a legal historian and writer of biographies who, in this short essay, has turned her attention to the work of one legal scholar, David B. Wexler, and his role in the development of the interdisciplinary field of therapeutic jurisprudence (TJ). The essay traces TJ's roots back to Wexler's undergraduate and law school education, but especially notes its emergence from his early academic work at the University of Arizona in mental health law. It pays close attention to Wexler's academic partnership with the late University of Miami law professor Bruce Winick , a close friend and academic partner, and describes how Wexler and Winick nourished the field through their close contact with mental health law professors and then with interdisciplinary and international scholars, judges, and practitioners. The essay tries to capture the richness and breadth of TJ and to bring it to life through an examination of various stages of Wexler's academic life, both in Arizona and now in Puerto Rico.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".