The Surrealism of Men’s Rights Discourses on Sexual Assault Allegations: A Feminist Reading of Kafka’s The Trial
Bibliographic record
Abstract
Being a feminist in the contemporary Canadian context, post-Ghomeshi, can lead to existential crises. In this paper I investigate this relationship of feminist activism and reality, men’s rights activism (MRA) and surrealism, and the Absurd via the work of surrealist novelist Franz Kafka. While Kafka’s The Trial is popularly understood as an allegory for the alienation and pains of bureaucracy and modernity, I posit a new interpretation of the story as a men’s rights perspective of sexual assault allegations. I use Shoshana Felman’s theory of integrated literary and legal visions to read Kafka’s The Trial against men’s rights discourses regarding sexual assault allegations. I find this theory of evidence and repetitions across the disciplines of art (Kafka) and law (the Ghomeshi trial) useful as analytical sites for critically engaging with men’s rights discourses about sexual assault allegations. I demonstrate how The Trial can be interpreted as a representation of the phenomenon of sexual assault allegations according to men’s rights discourses, and demonstrate how these discourses are just as surreal as Kafka’s story. Through the Ghomeshi verdict I will demonstrate how these surrealist fantasies impact real-world sexual assault accusations, trials, and court decisions.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.027 | 0.069 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 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".