Voicing an Opinion: Authorship, Collaboration and the Judgments of Justice Bertha Wilson
Bibliographic record
Abstract
In this paper, we spin the question “Will Women Judges Really Make a Difference?” in another direction. While “difference” is a big preoccupation for us, our interest is less in the question of whether or not men and women judge differently, than in the fact of difference between judges: “differences of opinion” between judges that find textual expression in the form of published dissenting opinions. Using Canada’s first woman Supreme Court justice as our point of departure, we consider the nature of judicial work. In Part II, looking at statistics, we sketch a portrait of Justice Wilson’s judicial work, attending to types of opinions (unanimous, majority, dissenting, concurring), and methods of participation (signing and authoring). We contextualize this portrait by considering Wilson’s work alongside that of colleagues with whom she sat. We follow two strands in this data. The first, very visible in Part II, focuses attention on particular judges, raising questions about difference, voice and identity. In Part III, influenced by the insights of institutional ethnography, we reflect on a second strand in the data, one that suggests room for more attention to the complex collaborative and institutional dimensions to the production of law. If the empirical snapshot can encourage attention to the role of difference in the work of Canada’s first woman Supreme Court justice, it should also encourage attention to the place of difference more generally in the making of law. The judgments of Justice Bertha Wilson can enable a robust discussion about the production of opinions, as well as nuance in our thinking about the implications of collaboration, authorship and voice.
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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 | 0.030 | 0.173 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.028 | 0.028 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.004 |
| 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".