Male Rape: Prevalence, Consequences, and Myths
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Disclosing abuse is a crucial step for survivors of all genders, as it is often made to individuals they trust and share intimacy with.
“Disclosing abuse is a crucial step for survivors of all genders, as it is often made to individuals they trust and share intimacy with [33, 42, 49].”
Rowan's disclosure of his abuse in adulthood within the community was largely met with negative and sometimes homophobic reactions, reflecting male rape myths.
“Rowan’s disclosure of his abuse in adulthood within the community was largely met with negative and sometimes homophobic reactions, reflecting male rape myths [33].”
The citation lists haven’t been fetched yet
References 77 · Cited by 4
- Authors
- Widanaralalage, B. K.
- Affiliations
- University of Westminster (GB)
- Corresponding author
- Widanaralalage, B. Kennath
- Venue
- Sexual Crime
- Publisher
- Springer International Publishing
- Published
- 2024
- Pages
- 93-117
- ISSN
- 2628-8168 (ISSN-L)
- 2628-8176
- OpenAlex
- W4396597700
- Cited by
- 4
- References
- 77
- Citations by year
- 2026: 1 · 2025: 3
- FWCI
- 15.66
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- Locations
- Sexual crime. (publishedVersion)
- Topics
- Social Sciences › Gender Studies › Sexual Assault and Victimization Studies
- Social Sciences › Psychology › Clinical Psychology › Psychopathy, Forensic Psychiatry, Sexual Offending
- Social Sciences › Health › Intimate Partner and Family Violence
- Keywords
- male rape, sexual violence against men, prevalence, psychological impact, masculinity, intersectionality, marginalized communities, sexual violence legislation, sociocultural factors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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