Bibliographic record
Abstract
Belleau and Johnson respond to the three articles in the Focus Feature. Agreeing with the general proposition that dissent matters, that it is valuable, and that it strengthens our system of law, they share ten theses on dissent. These theses touch on: dissent as a structural feature of our system; the linking of emotion and reason in the language of dissent; the articulation of tensions between principle and practice across different categories of dissent; the variable emergence of dissent across different legal topics; the need for attention to both heightened dissent and its absence; the impact of judicial identity on dissent; dissent as a (sometimes invisible) process rather than only a product; different currents with respect to dissenting practice at the trial, appellate, and Supreme Court levels; dissent as legal pedagogy; the role of the reader of dissent; and the place of dissent in nourishing the legal imaginary. In brief, they argue that lawyers, law professors, and the public more generally ought to attend to judicial dissent in order to engage with the ways that our system of justice operates, renews itself, and changes.
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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 | 0.018 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.030 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.013 | 0.019 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".