Provocation and `Homosexual' Advance: Masculinized Subjects as Threat, Masculinized Subjects Under Threat
Bibliographic record
Abstract
By applying queer and critical gender theories to the notion of the masculinized subject, this article theorizes the complexities of the `homosexual' threat within the Canadian legal domain of the provocation defence. The article remarks that most `homosexual' advance defences at the appellate level are rejected while only some are successfully believed. It argues that the extent to which appellate decisions have recognized this defence is predicated upon a logic of (hetero)normativity in which the threat of the `homosexual' advance is not homosexuality per se, but rather, symbolic feminization. This notion of symbolic feminization is theorized and tested through its application to appellate cases. The `homosexual' advance defence is most often rejected because it has the potential to destabilize the fiction of a (hetero)normative masculine subject as impenetrable. Nevertheless, in some appellate cases, the threat of symbolic feminization was ruled to be imminent and its deadly defence worthy of the court's consideration. In a unique case, R. v Valley (1986), the court located `homosexual' threat by recasting the violence of emasculation through the figure of the `S-M homosexual'. Fleshed out as predatory, sexually aggressive and hyper-masculinized, the `homosexual' could now pose an imaginable threat to normative masculinity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.058 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| 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".