Disciplining the Unruly: Sexual outlaws, Little Sisters and the Legacy of Butler
Bibliographic record
Abstract
This article examines the legal regulation of sex and sexuality through two landmark cases: R v. Butler, and Little Sisters Bookstore and Art Emporium v. Canada. With a focus on the ruling and arguments in Little Sisters, this article addresses Criminal and Customs prohibitions on obscene materials as an exercise in disciplinary governance, and discusses its particular effects on gay and lesbian sexuality. The Butler decision upheld the constitutionality of Criminal obscenity provisions and created the ‘community standards test’ to determine what would be considered harmful and obscene. In little sisters, Customs regulations based on the criminal provisions are challenged as discriminatory towards gay and lesbian sexually explicit materials. This article evaluates the arguments against the Butler test submitted in the Little Sisters challenge, and ultimately agrees with their conception of Butler’s harm principle as a vague, conservative and majoritarian morality unfriendly to marginal sexual expression. Finally, the article concludes that the court’s attempt to discipline marginal sexual expression as reinforced in Little Sisters will be ineffective as these sexual subjects are not disciplining themselves but are continuing to struggle, and because previously marginal sexual expression is increasingly normalized by other discourses such as mainstream media.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.042 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".