Charter Decisions in the McLachlin Era: Collegiality and Ideology at the Supreme Court of Canada
Bibliographic record
Abstract
This paper examines how justices on the Supreme Court of Canada voted in Charter appeals between 2000 and 2009. Charter appeals, at least in popular belief (and possibly also in theory), have the greatest potential to reveal voting that is influenced by extra-legal policy preferences. Confining the analysis to the time during which Chief Justice McLachlin has led the Court aids in controlling for the effects of a particular Chief Justice in assessing the roles of ideology and consensus. Several of the Court's members have exhibited sharply different voting proclivities in s.15 (equality rights) appeals as compared with Charter claims made in the context of criminal law appeals (and, indeed, other Charter appeals). This finding suggests that at least some of the justices on the Court have been influenced by policy preferences on at least some occasions in discrete areas of Charter rights adjudication. On the other hand, it also suggests that judicial policy preferences are richer and significantly more nuanced than can adequately be captured by a simple "right"-"left" or "conservative"-"liberal" characterization of these policy preferences. The paper discusses a number of implications of the analysis and findings.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".