Governing Through Harm to Promote Liberal Values: The Canadian Approach to Obscenity and Indecency Following R. v. Labaye
Bibliographic record
Abstract
This paper traces the history of the Supreme Court of Canada’s construction of harm(s) tests in the context of its obscenity and indecency jurisprudence from Hicklin (1868) through Labaye (2005). At the core of these tests is a functionality linked to presumptive societal norms. The contemporary harm assemblages are risk-based, and concern the maintenance of cohesion, organized in relation to the impact of obscenity or indecency on abstract political values rather than concretized sexual subjects. What is more, the Labaye Court has constituted an expanded harms-based test which reifies risk of harm as tantamount to proven harm while propagating the nimble lie that Courts are required to rely on expert opinion evidence of harm, when the Courts, in fact, rely on their own judgment. Ultimately, the Court is still concerned in the main with the proper functioning of society, targeting those whose conduct is deemed harmful to a particular view of society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".