Bibliographic record
Abstract
In this paper, I describe the face of modern civil justice and discuss four paradoxes which justify re-evaluating the role of the judge responsible for reviewing class action settlements, in light of modern judicial culture. I also critically evaluate the existing procedures applicable to the fairness review as well as the judicial role described in the caselaw and doctrine, before suggesting a revised, three-parted role for the reviewing judge in the class action settlement context. Ultimately, I suggest that to reach fairness of process and outcome in class action settlements, judges should remain active and creative in their inquisitorial assessment of proposed class action settlements. They should also remain conciliatory, participating in the search for solutions regarding the proposed settlement, always seeking to find the truth (and what is “just”) about the proposed settlement, in the utmost respect for the rights of absent class members, the respect of their interests, and the additional consideration of the interests of the defendants and of the public.
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 | 0.215 | 0.441 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.012 | 0.031 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".