Missing Privacy Through Individuation: The Treatment of Privacy in the Canadian Case Law on Hate, Obscenity, and Child Pornography
Bibliographic record
Abstract
Privacy is approached differently in the Canadian case law on child pornography than in hate propaganda and obscenity cases. Privacy analyses in all three contexts focus considerable attention on the interests of the individuals accused, particularly in relation to minimizing state intrusion on private spheres of activity. However, the privacy interests of the equality- seeking communities targeted by these forms of communication are more directly addressed in child pornography cases than in hate propaganda and obscenity cases. One possible explanation for this difference is that hate propaganda and obscenity simply do nor affect the privacy interests of targeted groups and their members. In contrast, this paper suggests that this difference in approach reflects the adoption of an individualistic approach to privacy that may unnecessarily place it in tension with equality. In so doing, it sets the stage for an exploration of more social approaches to privacy that may better enable exploration of privacy's intersections with equality and its collective value to the community as a whole.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.043 | 0.065 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".