Performer Demographics (Portrayals of Sexuality in Pornography)

Pornography is a fictional media genre that depicts sexual fantasies and explicitly presents naked bodies activities for the purpose of arousal (Williams, 1989; McKee et al., 2020). Regarding ethics effects, pornography has traditionally been viewed as highly problematic. Pornographic material accused portraying sexuality in unhealthy, morally questionable often sexist ways, thereby harming performers, audiences, society at large. In age Internet, become more diverse, accessible, widespread than ever (Döring, 2009; Miller Consequently, depiction focus growing number content analyses both mass (e.g., erotic pornographic novels movies) social stories, photos videos shared via online platforms). Typically, pornography’s portrayals are examined by measuring prevalence frequency practices or relational dynamics related gender roles quantitative analysis (for research reviews see Carrotte 2020; & McBain, 2022). This entry focuses on representation performer demographics (such sex/gender, age, race/ethnicity) one eight important dimensions pornography. Field application/theoretical foundation: field research, different theories used, mainly 1) general effects theories, 2) 3) role, feminist queer 4) fantasy desire 5) mold versus mirror theories. The DOCA “Conceptual Overview (Portrayals Sexuality Pornography)” introduces all these explains their application to respective applicable dimension References/combination with other methods data collection: Manual can be combined qualitative Keft-Kennedy, 2008) well computational Seehuus 2019) analyses. Furthermore, complemented interviews surveys investigate perceptions evaluations among creators performers West, audiences Cowan Dunn, 1994; Hardy 2022; Paasoonen, 2021; Shor, Additionally, experimental studies helpful measure directly how perceived evaluated recipients, if affect audiences’ sexuality-related thoughts, feelings, behaviors Kohut Fisher, 2013; 2019). Example manual analyses: Common hypotheses relation state portrays manner entailing violence towards degradation women, usually perpetrated men. addition, it hypothesized asymmetric terms showing men superior dominating, women subordinate submissive, positions. sex/gender asymmetry reflected demographic variables such status (difference) (difference). mainstream critized its racist portrayal sexuality. means non-White underrepresented they represented depicted according racial/ethnic stereotypes. To test code accordingly, necessary clarify concepts race/ethnicity use valid reliable measures. It note context researchers conceptualize characteristics differently two approaches coding available: Direct based person’s appearance apparent skin color) indirect meta-information about material, sub-genre category belongs “Asian” displaying Asian-looking “Teen” adult who look very young). If applying an intersectional theoretical framework (see Pornography)”) researcher would need each multiple variables. Coding Material Measure Operationalization (excerpt) Reliability Source Sex/gender: Most way portrayed hypothesize (or, least, acknowledge possibility) likely perpetrators violent recipients behaviors). Accordingly, essential addressing questions this area. term preferred when referring people groups, reflects categorization, whereas sex biological categorization (American Psychological Association, While many address differences do not present any standardized measures variable sex/gender. presented below rare exceptions, but remains vague instructions meanings value “other”. N=50 segments (length 20 min. each) from random sample 50 bestselling films (1 segment per film) depicting total 1,109 Sex/gender (based appearance) “Coder’s perception character’s primary secondary characteristics.” Polytomous (1: male; 2: female; 3: other). Cohen’s Kappa: 1.0 Willis al. (2020) Age: Performer may interest own right investigating whether bias toward early 20s). Alternatively, recorded differential depictions group younger female submissive older performers). should noted performer’s (as case legal “Teen”, where young characters played performers; al, (of performed character) difficult tools make-up, costume, lighting, filters greatly impressions. problem available cannot ensure sufficient reliability. best-selling DVDs Australia 2003 838 scenes Age age. 18-30 years; 31-40 41-50 4: 51+ years). Not (2008) character age—not actor’s—based physical appearance.” Note: some were clearly intended under 18 years actors older. <18; 18-20; 21-30; 31-40; 5: 41-50; 6: >50 .47 Race/Ethnicity: Critical racism mere visibility races/ethnicities stereotypes, Black being sexually aggressive well-endowed Asian petite, docile (Miller N=269 popular PornHub.com categories Race/ethnicity category) Videos selected/coded race/ethnicity-related PornHub. “Asian/Japanese” PornHub categeory; “Interracial” category; “Ebony” “Latina” category). Shor Seida (2019) N=45 15 websites (3 website) Performers coded appearance. Binary White; non-White/other race). Gorman (2010) race Black; Asian; Latina/o; Native American; .94 ReferencesAmerican Association. (2020). Publication American Association (7th ed.).Carrotte, E. R., Davis, A. C., Lim, M. S. Sexual pornography: Systematic review narrative synthesis video Journal Medical Internet Research, 22(5), Article e16702. https://doi.org/10.2196/16702Cowan, G., K. 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