"ITT: Rape Analysts": Hosting Negotiations of Consent, Kink, and Violence in Virtual Space
Bibliographic record
Abstract
This project examines the use of virtual space in navigating the meaning of consent after the fact.Recently, some individuals have begun to interrogate their own past sexual experiences through the use of online sex education forums, blogs, and subreddits.Through this process of eliciting community feedback, many have (re)framed these experiences as consensual or nonconsensual.Using data that was obtained from five distinct Reddit communities (or subreddits), comprised of 66 posts and over 4,000 comments, this thesis examines this process as both an extralegal, reflexive negotiation of consent, and a user-constructed virtual trial.This discussion posits that the use of these spaces (rather than traditional legal/institutional resolutions) is a response to the significant changes in how consent has been conceptualized within the mainstream; this is exemplified through academic literature theorizing consent and the shifts in Canadian governance of sexual assault.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.021 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".