Studying Rape: The Production of Scientific Knowledge about Sexual Violence in the United States and Canada
Bibliographic record
Abstract
In 1987, statistics transformed rape from a rare and personal concern into an epidemic in popular consciousness. Mary Koss and colleagues conducted victimization surveys with thousands of college women, 1 in 4 of whom reported completed or attempted rape. This finding received tremendous attention in the 1980s, and continues to influence activists and state officials. Notwithstanding the importance of this and other scientific facts, scholars have rarely explored the role of scientists in shaping perceptions of and responses to sexual violence. This project addresses that gap in the literature, via the following questions: (1) how have scientists conceptualized sexual violence among adults; and (2) what social mechanisms enable, constrain, and otherwise influence scientific research on sexual violence? Drawing on insights from feminist science studies, I approach sexual violence as an intra-active phenomenon, and regard objects of study (sexual violence) as inseparable from agencies of observation (research instruments, researchers). Data came from three sources: content analysis of journal abstracts (N=1,313), in-depth assessment of texts in different subfields (N=84), and interviews with researchers (N=31). Ultimately, I argue that sexual violence research has been dominated by psychological inquiries, as well as gendered assumptions regarding who is most capable of perpetrating and experiencing rape. Scientists have produced a tremendous body of knowledge regarding the individual-level causes, individual-level outcomes, and prevalence of men’s sexual aggression toward women. Systemic forces and sexual violence that deviates from this particular gendered pattern remain underexamined. I further argue that scientific research on sexual violence is shaped by a range of social mechanisms that are particular to fields associated with questions of social morality and social movements including feminism(s).
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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 | 0.024 | 0.098 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.016 | 0.021 |
| Science and technology studies | 0.021 | 0.015 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".