Don't Go to Lawyers for Moral Guidance
Bibliographic record
Abstract
If it were followed by “I’m a president,” Richard Nixon’s televised denial (“I am not a crook”) would be tantamount to Jimmy McGill’s self-portrayal in Better Call Saul. Out of the crooked timber of humanity, an honest president or an ethical lawyer rarely emerges. They’re like needles in a haystack. Nevertheless, it’s worthwhile to search for these rare artifacts and, in the process, ask, “Why do so many lawyers (and presidents) fall from grace, transforming into morally bad or corrupt actors?” The ability to be a good or ethical person can deteriorate over time. In their personal and professional lives, people can make consistently poor choices in their capacity as moral agents. In turn, they cultivate flawed habits or what are often referred to as vices. Jimmy McGill’s trajectory is, without a doubt, a harrowing story of moral decline. In some ways, his transformation into Saul Goodman resembles a trite story about how a profession, lawyering, corrupts its practitioners. On a deeper level, McGill’s journey involves a fundamental change in how he habitually interacts with his environment, a change of motivation and disposition that is, almost entirely, a change for the worse. To know the content of Jimmy’s character is to be familiar with his story, a story of moral decline and ethical failure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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 teacher head, 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".