Bibliographic record
Abstract
If every court achieved 99.9 percent quality for litigants, should we be satisfied? In other endeavors, if 99.9 percent was the standard of excellence, the IRS would lose two million documents this year, 3,056 copies of tomorrow’s Wall Street Journal would be missing one of three sections, and 12 babies would be given to the wrong parents each day. For those industries, 99.9 percent is not good enough and it cannot be acceptable for courts either. Judicial excellence is a mindset. It must be an obsession or, as Aristotle said, “Quality is not an act. It is a habit.” Today being a judge is a 24/7 job. Judges are viewed as leaders in our community. We are, in a sense, role models in an era where it is very difficult to be a role model. The political rhetoric of our time has become so heated and polarized that trust and confidence in courts is jeopardized. The high-spending judicial races of some states are problematic but, lest anyone become complacent, even in Canada there are instances of political figures rather unfairly criticizing courts.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.539 | 0.534 |
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".