Bibliographic record
Abstract
This paper defends the claim that there are two previously underexplored ways in which pornography silences women. These ways that pornography silences are (1) the smothering of refusal and (2) the smothering of sexual assault reports, and they can be explained in part through Kristie Dotson’s account of “testimonial smothering.” Unlike the work of other writers in the pornography as silencing literature, my discussion of silenced refusal of sex deals with the cases where women have said yes to sex but would have said no if they had felt that they could have. I show that this, and cases where women do not report sexual assault, count as testimonial smothering through identifying rape myths as a species of “pernicious ignorance.” I make the connection to pornography in presenting evidence that pornography contributes to acceptance of rape myths. This takes us to my general conclusion: Dotson’s account of testimonial smothering gives us a way in which pornography contributes to the silencing of women, by silencing their refusal of sex and their reports of sexual assault.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".