Sex in Ohio mo

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Search for more articles by this author. Objective: Sex trafficking is a pressing issue in Ohio—a major node in national sex trafficking networks; however, no quantitative analysis of risk factors specific to Ohio victims has been conducted.

Variables of specific interest include peer influence, experiences during transience, prior minor victimization, and a lack of support while attempting to escape. : Survival sex and peer influence increase the odds of minor victimization, and a lack of available support and resources for victims while attempting to escape ificantly increase the odds of adult victimization.

In addition, these have been used in a report to an Ohio Senate Caucus promoting a federal bill regarding missing children. Department of State, ; U. Department of Justice, Department of State, The enumeration measures and methodologies used to approximate these hidden and underground populations, if elucidated, are by no means definitive and are thus subject for debate; therefore, these estimates should be considered with caution. This article focuses on domestic sex trafficking in the United States, which is defined by the U.

Victims of Trafficking and Violence Protection Act of as an inducement into committing commercial sex acts by force, fraud, or coercion, or when persons induced to perform sex acts are under 18 years old. Under the federal law, those who profit from commercial sex acts performed by persons under their control by means of force, manipulation, or coercion, traditionally known as pimps, are now referred to as traffickers Williamson, Karandikar, et al. In this study, respondents were identified as trafficking victims if they affirmatively responded to the following: a currently or ly self-identified as a trafficking victim, b was forced into the sex industry by a trafficker or agent acting in their place, such as a boyfriend or family member, or c sold sex at age 18 years or younger, but did not self-identify as a trafficking victim.

This study analyzed direct sex trafficking risk factors in Ohio within a life-course theory framework. Life-course theory was used to identify and systematize direct minor and adult sex trafficking risk factors, whose impact on outcomes were measured using multivariate logistic regressions on a representative sample of Ohio urban, street-based sex workers.policy implications, and future research suggestions are discussed. Ohio hosts an extensive commercial sex market, including domestic and international trafficking victims, due in large part to its strategic location as an interstate transportation node.

Further, Ohio contains concealed sex markets operating at migrant camps, pornography studios, and truck stops. The state also has the fifth highest of strip clubs in the country Krauss, ; National Human Trafficking Resource Center, n. Williamson, Karandikar, et al.

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The Polaris Project n. The state responded in by passing Senate Billwhich rendered human trafficking a standalone felony offense and established provisions for educating law enforcement on human trafficking issues, such as requiring data collection on convictions and providing protection for victims Ohio Senate Bill; Perdue et al. In Junethe Ohio Legislature enacted safe harbor laws as part of House Billmeaning minors arrested for selling sex were no longer treated and prosecuted as criminals, but considered victims of child abuse Ohio House Bill Despite the passing of these anti-trafficking laws, as well as the committed work of activists, domestic sex trafficking persists in Ohio.

Further, an additional 3, Ohio girls are at risk of trafficking; this risk is especially high for runaways who have been missing from home for more than 2 weeks Williamson, Karandikar, et al. Estimates for Ohio women trafficking victims remain elusive Williamson, Karandikar, et al. This study sought to measure the effect of direct risk factors for minor and adult domestic sex trafficking on the odds of trafficking outcomes.

Reid separated these two types of risk factors by developing a structural equation causal pathway model of sex trafficking victimization, beginning with caregiver strain e. Moreover, negative emotions arising from past trauma directly increased vulnerability to victimization Reid, Specifically, Reid identified a statistically ificant casual pathway from children running away from home to minor sex trafficking victimization, beginning with childhood maltreatment, neglect, and sexual abuse.

The time and place of life experiences entail the effect of historical events e. The timing of life events is termed transitions ; the times between transitions are known as durations Elder et al. The timing of life events is a particularly important component of life-course theory because immediate situational adaptations potentially place individuals on life-long trajectories.

Antisocial behaviors e. Social capital or the lack thereof motivates or dissuades antisocial behavior.

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For example, stable employment diminishes the attractiveness of theft or financially-motivated crime, whereas chronic unemployment amplifies the appeal of informal and underground occupations. The main structural factor affecting minor trafficking outcomes is negative childhood and adolescent informal social control processes, which are managed by personal traits.

Negative childhood and adolescent informal social control processes include poor school performance, family dysfunction, running away or being forced from home, homelessness, engaging in survival sex, having family or friends in the sex trade, juvenile detention, childhood abuse, early drug or alcohol use, and placement in foster care Reid, a.

Table 1. Adult risk factors are structurally motivated by a lack of social capital, independent from negative informal social controls Reid, a. Domestic adults often accept victimization as a means to support dependents particularly children from teenage pregnancies or as the result of coercion or abandonment by abusive romantic partners. The analysis involved testing several hypotheses based on the theoretical framework and two less-directed suppositions, or subhypotheses, created to test commonly-held logics regarding the role of race and age on sex trafficking outcomes.

This study relies on two multivariate logistic regression models to test the hypotheses while ing for other theoretical minor- and adult victim-specific risk factors using a representative sample of urban, street-based sex workers in Ohio. A list of risk factors available for the minor and adult models is presented in Table 1.

The analysis in this study used data obtained from a U. The majority of the questionnaire was formatted as binary responses i. A full descriptive analysis of the survey can be found in Williamson, Karandikar, et al. Data collectors worked with trained advocates at collection sites in private and secure library study rooms. Contributors younger than 18 years were reported to child welfare. Questions were reworded and repeated during the survey to assess consistency and reliability; those with vast discrepancies were removed. A demographic overview of the survey respondents can be found in Table 2.

Table 2. Respondents were obtained using respondent-driven sampling RDSwhich involves initial participants passing the survey onto others within their cohort i. Social network connections between respondents are recorded to calculate the amount of homophily i. Coupons could be redeemed at convenient locations within each city on specified days and times. Regrettably, data from Youngstown and Chillicothe were unable to be collected because of a lack of seed referrals.

Cincinnati and Dayton covered The typology of sex workers represented in the survey was ascertained by examining their self-identified work environments and income levels. Admittedly, work environments do not completely define the type of sex worker; therefore, self-reported annual household income was used as an additional criterion. Department of Health and Human Services U. Census Bureau, n. Lower income respondents are likely represent informal or street-based workers earning low and subsistence-level incomes, whereas the uppermost income class probably represents high-end escorts.

False responses are often elicited when participants are confronted with questions on sensitive topics or queries that present conflicting interests, such as abuse or criminal activity. To mitigate this problem, questions regarding trauma most would feel uncomfortable discussing or disclosing with strangers were avoided, particularly rape, childhood sexual abuse, and abuse from traffickers or clients. All variables are affirmative responses to the respective event or descriptor, dummy-coded as 1. Age was the only continuous variable. The analysis used two multivariate logistic regression models.

The dependent variables were dichotomous i. Therefore, either logistic or probit regression models should be considered. Logistic regression was chosen because its coefficients are more easily interpretable as odds ratios than probit marginal effects, and because no theoretical foundation exists to select the probit link function, which assumes the latent factors generating the dependent variable are normally-distributed.

Baseline models consisted of the hypothesized risk factors and control variables; additional risk factors were included based on their statistical fit in the model. Logistic regression generally abides by the heuristic rule of 10meaning 10 dependent variable outcome events are required for each explanatory variable. Vittinghoof and McCulloch discovered the rule of 10 can be relaxed to five events per-variable with minimal effects on bias and efficiency.

Compromising at seven events per-variable, as many as nine variables were permitted in the minor trafficking risk model and eight variables in the adult trafficking risk model. Missing data were evident, but not a major concern. Two respondents did not report their current age, and therefore, those observations were excluded from the adult trafficking dataset. To ensure the veracity of the models, coefficients were estimated with robust standard errors and multicollinearity, goodness-of-fit, and model specification tests were performed.

Multicollinearity was managed by ensuring the variable inflation factor was less than five and the condition was under Wald tests determined whether the model statistically ificantly differed from complete randomness. In addition, each model was required to pass the Hosmer-Lemeshow goodness-of-fit test, as recommended by Peng, Lee, and Ingersoll The following five factors increased the odds of being forced into minor sex trafficking: Engaging in survival sex, having friends who bought or sold others for sex, difficulty in school before sex work, spending time in juvenile detention, conflict with parents before involvement in sex work, and ascribing as multiracial.

Engaging in survival sex while running away had the greatest effect, increasing the odds of being forced into sex work as a minor by approximately 2. Respondents having friends who bought or sold others for sex had 2. conflict with parents increased the odds of minor victimization by 1. When compared with African American respondents, the multiracial control variable increased the odds of being a minor trafficking victim by 1. Table 4.

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The adult sex trafficking risk model produced seven statistically ificant coefficients: homelessness before involvement with the sex trade, unsuccessfully attempting to exit sex work, not trying to exit sex work, current age, and two of the race control variables White and Hispanic. Adult trafficking victims who attempted to leave sex work but did not find help in doing so were at 2. Victims who did not seek help were at 0. The odds of being currently trafficked decreased by approximately 0. The odds a White adult is currently being trafficked are about 2. This study used a representative sample of Ohio urban, street-based sex workers to measure the effect of direct risk factors for minor and adult sex trafficking on empirical victimization outcomes.

The estimates provide a suitable inferential basis to discuss and prioritize sex trafficking risk factors, particularly regarding the role of survival sex on minor victimization and the availability of assistance for escaping victims on adult victimization, which can be used to direct future research and potentially motivate anti-trafficking policy and programming in Ohio. Both sex trafficking models produced statistically ificant variables and validated the majority of the hypotheses.

Sex in Ohio mo

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