Bibliographic record
Abstract
I recently walked past a student bulletin board at my law faculty and saw an Association of Trial Lawyers of America Law Student Membership Program poster with following headline: ''Trial lawyers don't just practice law. They live it. The association self-described as the world's largest trial bar - elsewhere states that: ''The art of advocacy demands your total involvement and dedication.Similar statements about law's all-encompassing demands surround us in law school and at bar. A number of years ago, I was at a meeting of associates at a law firm in Toronto. Two senior lawyers called meeting with a view to discussing career strategies and life at bar. It was a brief, collegial meeting. A number of issues were discussed. However, comment that stuck in my mind was suggestion that life in law becomes a lot easier if you allow line between your professional and personal lives to fade away.
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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.034 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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".