‘Talk, listen, think’: Discourses of agency and unintentional violence in consent guidance for gay, bisexual and trans men
Bibliographic record
Abstract
Attention to men’s attitudes towards sexual consent and violence has led to sexual consent guidance targeting men specifically. This article examines conflicting notions of consent and the construction of implied readership in a UK corpus of online sexual consent guidance for gay, bisexual and trans men. ‘Positive consent’ discourse presents consent as free, active and able to be withdrawn. ‘Talk, listen, think’ discourse recommends clear and explicit communication about boundaries. I argue that these discourses present gay, bisexual and trans men as effective moral agents, but these conflicting discourses also weaken the message of consent as free and affirmative. I show how synthetic personalization constructs solidarity between the implied reader and an imagined community of gay, bisexual and trans men who share the aim of ending sexual violence, but also constructs solidarity with men who are presented as unintentionally violent. I conclude by suggesting ways to improve consent guidance.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.048 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| 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".