The Plays: The Thing - The Medieval Courtly Lesson: Law And Lawlessness
Bibliographic record
Abstract
The following is an offshoot of a talk I presented at the 1990 Popular Culture Association conference in Toronto. In this essay I will introduce a play I wrote, Tristan and Isolde and will describe the impact of the Celtic legends to my own academic discipline, law. Celtic and Arthurian legends are immortal. If the legends can survive the societal changes brought on by modern technology they can and will survive anything and for all time. There is still awe at the thought of King Arthur's sword Excalibur -- even in the face of semi-automatic handguns and the fully automatic Uzi. The Lambhorgini, Corvette Stingray, and DeLorean have failed to displace the charm of the knight's horse. Furthermore, bulletproof vests, tanks, and the like have failed to blanche from our collective memories the meaning and beauty of armor. And finally, neither Kim Bassinger, Christi Brinkley nor the like have diminished our romantic admiration of Queen Guinevere or Lady Isolde. Of course, the legends are immortal not because of the sword, horse, or armor; but rather because of the personalities in the legends and what they can teach us about daily life. Humans are essentially alike. Our differences from one another are in particulars, not in generalities. Thus, the simple man can learn from the famous woman; and the celebrity can learn about life from the blue collar worker.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.038 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".