What’s in a label? Exploring rape myth and rape culture discourses embedded in perceptions of victims and survivors
Bibliographic record
Abstract
Feminist scholars have long asserted that the label assigned to someone after an experience of sexual violence (e.g., victim or survivor) can shape personal outcomes due to the internalization of societal perceptions of these labels. While there is a growing body of literature on the effects of self-labelling, the societal perceptions of victims and survivors are less explored, with little understanding as to how dominant discourses such as rape culture and rape myths are embedded into these perceptions. Adopting from critical discourse analysis and feminist poststructuralism, we offer critical feminist poststructuralism (CFPS) as a useful framework for understanding discursively shaped societal perceptions of victims and survivors. Considering the presence of rape culture and rape myths on university campuses, we set out to explore the potentially mediated nature of rape myths and rape culture discourse and perceptions of victims and survivors among undergraduate students. Electronically submitted responses to an online prompt were analyzed using CFPS to explore how victim and survivor discourses were activated through language and institutional and social discourses of rape culture and rape myth. We describe four dominant threads of discourse from our analysis that suggest sexual violence labels function as regulatory mechanisms for rape myth and rape culture discourse. The findings highlight the need for continued applied work on the multiplicity of victim and survivor identities produced through rape culture and rape myth discourse.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".