An Attractive Target: Do Perceptions of Physical Attractiveness Shape Victimization Risks in Women’s Prisons?

ABSTRACT

Emerging research suggests that physical attractiveness may yield outcomes beyond preferential treatment, such as increasing the vulnerability to victimization during adolescence. Despite growing awareness of individual and institutional victimization risk factors during incarceration, research has yet to consider the role of physical attractiveness. Drawing on survey data collected from 223 women across two Pennsylvania prisons, this article investigates whether perceptions of physical attractiveness operate as protective or risk factors for victimization experienced while incarcerated. Logistic regression results show a significant positive association between interviewer-assessed perceptions of physical attractiveness and incarcerated women’s self-reported resident-on-resident victimization. Dominance analysis results indicate that perceptions of physical attractiveness ranked nearly as high as histories of abuse in predicting incarcerated women’s risk of victimization. This study uncovers an unintended consequence of physical attractiveness for imprisoned women, demonstrating their heightened susceptibility to in-prison victimization.

KEYWORDS:

• Women’s incarceration
• resident-on-resident victimization
• physical attractiveness
• physical appearance

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Four women opted out of answering victimization questions, leaving us with a final sample size of 219.

2. Models with little predictive power have a McFadden’s R² closer to 0, with values between 0.2 and 0.4 representing excellent model fit (McFadden, 1974).

3. Complete dominance is when a predictor contributes more to McFadden’s R² than another predictor across every possible subset model comparison. Conditional dominance statistics average each predictor’s marginal contribution to McFadden’s R² within an order, where an order is the model size or the number of predictors in a subset model. General dominance statistics average conditional dominance statistics between orders for each predictor.

Additional information

Funding

The work was supported by the National Institute of Justice [2016-MU-MU-0011]; National Science Foundation [1457193]; Penn State Criminal Justice Research Center.