The Rise and Fall of Freedom of Expression in the Mclachlin Court
Bibliographic record
Abstract
This paper evaluates the scope of protection of freedom of expression during the McLachlin court. In Part I, attention will be given to the free expression cases in which Beverley McLachlin has participated, both as a judge and then as Chief Justice. This quantitative analysis sheds light on how often she has ruled in favour of the rights claimant and whether that rate has fluctuated throughout the years. Part II dives into the question of the alleged reversal of her position through an analysis centred on her reasons in hate speech, falsehoods, and violent expression cases, and a critique of those decisions. In Part III, several hypotheses are drawn as to what drove the Chief Justice to sign onto the Court’s opinion, penned by Rothstein J., in Whatcott — most of which circle around her desire to enhance consensus within the Court. Finally, in Part IV, a thorough examination of her record with regard to expression involving obscene speech will demonstrate that the nature of the expression at issue played a role in the extent to which she emphasized the importance of strongly protecting freedom of expression.
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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 | 0.023 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.050 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".