Say Hello to My Little Friend: an Investigation Into the Correlations

Say Hello to my Little Friend: An Investigating into the

Correlation between Genital Slang and Sexism

A thesis submitted to the

Graduate School

of the University of Cincinnati

in partial fulfillment of the

requirements for the degree of

Master of Arts

in the Department of Sociology

of the College of Arts and Sciences

William M. LeSuer II

B.A. Kent State University

November 2011

Committee Chair: Erynn Masi de Casanova, Ph.D.

Abstract

A number of scholars in the social sciences have argued that slang terms for the genitals have a deleterious effect on those who use them or are exposed to them by promoting and maintaining heteronormative, androcentric views of sexuality and gender. Sociolinguists, especially second-wave feminists, persuasively argue that our language is sexist and reflects and reinforces our patriarchal society. However, no research has been conducted to test whether the users of these words hold these views. This study seeks to answer whether there is a significant correlation between genital slang and sexist attitudes. (Partial correlations are used instead of regressions because the causal order is unclear.) Additionally, it explores the importance of demographic characteristics in the knowledge, use, and perceived offensiveness to genital slang.

When genital slang variables were regressed on demographic characteristics, gender was the primary source of significant differences. Significant correlations between the genital slang variables and sexism were found while controlling for demographic characteristics. However, the significant findings between the slang and sexism variables were puzzling at times. Some findings supported the theories and assertions of previous scholars that genital slang is patriarchal and heteronormative and correlates with sexist attitudes, while other findings eluded immediate explanation.

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Acknowledgements

I would like to thank all those who have helped me through this learning process. To my advisers Erynn Masi de Casanova, Ph.D. and Steve Carlton-Ford, Ph.D., thank you for your tireless effort and boundless patience. This paper would not have been possible without your support. It was an honor to work with you. I have grown as a scholar and a person because of you. To my family, friends, and cohort, thank you for your support and feedback. Your interest, awkward laughs, and skepticism strengthen my resolve and helped me push forward. To all the professors at The University of Cincinnati, thank you for your support and entertaining my surprise office visits. To Linda Kocher, thank you for being a good friend and listening to me at all hours of the day. The functioning of the department rests on your shoulders. Finally, to my

Katie Schutte, my wonderful fiancée, thank you for putting up with me through this and more.

Your love has kept me going through thick and thin.

TABLE OF CONTENTS ABSTRACT…………………………………………………………………………………… ii ACKNOWLEDGEMENTS…………………………………………………………………… iv LIST OF TABLES ……………………………………………………………………………. vii INTRODUCTION ………………………………………………………………………………. 9 LITERATURE REVIEW ……………………………………………………………………… 10 HYPOTHESES ………………………………………………………………………………… 17 METHODS …………………………………………………………………………………….. 17 Benefits and Limitations of Using Surveys …………………………………………………. 23 FINDINGS ……………………………………………………………………………………... 24 Demographics ………………………………………………………………………………. 24 Slang ………………………………………………………………………………………... 26 Male Genital Terms ……………………………………………………………………... 26 Female Genital Terms ………………………………………………………………….... 29 Sexism ………………………………………………………………………………………. 33 Hypothesis 1 ………………………………………………………………………………… 38 Male Genital Slang Categories ………………………………………………………….. 42 Female Genital Slang Categories ……………………………………………………….. 43 Hypothesis 2 ………………………………………………………………………………… 47 Hypothesis 3 ………………………………………………………………………………… 52 Male Genital Slang Categories ………………………………………………………….. 57 Female Genital Slang Categories ……………………………………………………….. 59 Hypothesis 4 ………………………………………………………………………………… 62 Male Genital Slang Categories ………………………………………………………….. 67 Female Genital Slang Categories ……………………………………………………….. 68 DISCUSSION ………………………………………………………………………………….. 72

Hypothesis 1 ………………………………………………………………………………… 73 Hypothesis 2 ………………………………………………………………………………… 76 Hypothesis 3 ………………………………………………………………………………… 77 Hypothesis 4 ………………………………………………………………………………… 78 CONCLUSION ………………………………………………………………………………… 81 FOOTNOTES ………………………………………………………………………………….. 84 BIBLIOGRAPHY ……………………………………………………………………………… 86 APPENDICES …………………………………………………………………………………. 89

LIST OF TABLES Table 1: Descriptive Statistics of Demographic Variables …………………………………….. 25 Table 2: Descriptive Statistics of Variables Measuring Male Genital Terms …………………. 27 Table 3: Descriptive Statistics of Variables Measuring Female Genital Terms ……………….. 31 Table 4: Descriptive Statistics of the Sexism Scale Subscales ………………………………… 35 Table 5: Number of Items and Cronbach's Alpha Coefficients for Extracted Sexism Scale Factors with Crossloaded Items Placed In Different Factors to Determine Changes in Alpha ………… 38 Table 6: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Male Genital Term Variables Are Regressed on Demographic Variables ……………… 40 Table 7: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Female Genital Term Variables Are Regressed on Demographic Variables …………… 41 Table 8: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Authority Categories for Male Genital Slang Terms Are Regressed on Demographic Variables ………………………………………………………………………... 43 Table 9: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Abject and Euphemism Categories for Female Genital Slang Terms Are Regressed on Demographic Variables …………………………………………………………. 44 Table 10: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Nonsense and Euphemism+Nonsense Categories for Female Genital Slang Terms Are Regressed on Demographic Variables ……………………………………………... 45 Table 11: R2, Adjusted R2, F-Test Values, Χ², Nagelkerke R2, Unstandardized Coefficients, Log Odds, and Significance Values when Dummy Variable for the Listing of “Cunt”, Use of “Cunt”, and Perceived Offensiveness to “Cunt” Are Regressed on Demographic Variables ………….. 46 Table 12: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Ambivalent Sexism Inventory Subscales are Regressed on Demographic Variables …... 48 Table 13: Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Modern Sexism Scale Subscales are Regressed on Demographic Variables …………… 49 Table 14: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Sexual Beliefs Scale Subscales are Regressed on Demographic Variables ……………... 50 Table 15: Correlations and Significance Values Between Male Genital Term Variables and Sexism Scale Subscales ………………………………………………………………………... 53

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Table 16: Correlations and Significance Values Between Female Genital Term Variables and Sexism Scale Subscales ………………………………………………………………………... 54 Table 17: Correlations and Significance Values Between Danger Category Variables for Male Genital Slang Terms and Sexism Scale Subscales …………………………………………….. 58 Table 18: Correlations and Significance Values Between Euphemism Category Variables for Female Genital Slang Terms and Sexism Scale Subscales …………………………………….. 60 Table 19: Correlations and Significance Values Between Listing of “Cunt”, Use of “Cunt”, and Perceived Offensiveness to “Cunt” and Sexism Scale Subscales ……………………………… 61 Table 20: Partial Correlations and Significance Values Between Male Genital Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables ………………….. 63

Table 21: Partial Correlations and Significance Values Between Female Genital Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables ………………….. 65

Table 22: Partial Correlations and Significance Values Between Danger Category Variables for Male Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables ………………………………………………………………………... 67 Table 23: Partial Correlations and Significance Values Between Danger Category Variables for Female Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables ………………………………………………………………………... 69 Table 24: Partial Correlations and Significance Values Between Nonsense Category Variables for Female Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables ………………………………………………………………………... 70 Table 25: Partial Correlations and Significance Values Between Listing of “Cunt”, Use of “Cunt”, and Perceived Offensiveness to “Cunt” and Sexism Scale Subscales ………………… 71

viii Introduction

Language connects the individual to the social structure. The importance of language in sociology and its theories cannot be understated. Language is used in all manner of schools of theories from Marxism to structuralism to functionalism to symbolic interactionism. Second- wave feminists seized upon the importance of language in shaping and maintaining societal beliefs and practices in America (e.g., Schulz 1975; Thorne and Henley 1975; Lakoff 1990).

These feminists and sociolinguistic scholars persuasively argue that language reflects the patriarchal and sexist nature of American society (Schulz 1975; Thorne and Henley 1975;

Spender 1985; Lakoff 1990). They further argue that without change, sexist language will continue to reify and perpetuate the gender inequalities that pervade American society (e.g.,

Schulz 1975).

Patriarchy permeates every aspect of our society and the people within it; our bodies are gendered by society and thus subjected to the same superior/inferior dichotomies prevalent in our society. Bodies are also a primary source of the taboo (for more on this, see the works of anthropologist Mary Douglas). The products and processes of our bodies are often deemed uncivil, rude, and unruly. Language which refers to these products and processes, in particular sexual ones, is similarly taboo and subject to euphemism and dysphemism1. The simultaneous gendered and taboo nature of sexual body parts and processes gives rise to a unique convergence of sexist and taboo language. From this a plethora of terms, collectively called “slang,” for the genitals (by which I mean any non-medical terms including swear and curse words, euphemisms, nonsense terms, pejoratives, etc.) has arisen.

Previous scholars studying genital slang have questioned but not tested whether there is a connection between genital slang and sexist attitudes and beliefs. The primary purpose of this research is to answer that very question. Additionally, this study tests whether various demographic characteristics affect the knowledge, use, and perceived offensiveness of genital slang. Some of the findings are puzzling and do not lend themselves readily to explanation, while others support the feminist claim that language reflects our patriarchal society.

Literature Review

Societies have gender norms and stereotypes that are communicated through language; the USA is no exception (Thorne and Henley 1975; Spender 1985; Lakoff 1990). Stereotypes and clichés, such as men being active and instrumental and women being passive and receptive, are pervasive throughout our society and reflected in our language (Thorne and Henley 1975;

Spender 1985; Lakoff 1990). Patriarchy, the dominance of males in society and the perpetuation of that dominance, is evident in our language as well (Thorne and Henley 1975; Spender 1985;

Lakoff 1990). An aspect of patriarchy is the systematic subjugation of women, which is also evident in how both men and women speak and in what they say (Schulz 1975; Thorne and

Henley 1975; Spender 1985; Lakoff 1990). Spender states that patriarchy is “characterized by male dominance and the means – both actual and symbolic – of perpetuating this dominance”

(1985:15) and that language plays a role in this perpetuation. Moreover, words relating to women are more frequently negative in nature, whereas words relating to men tend to be more positive (Thorne and Henley 1975). Schulz (1975) gives comparative illustrations of terms referring to women that have become pejorative, whereas parallel terms referring to men have not. Schulz refers to this as “the semantic derogation of women” (1975:64). For example, terms for elderly men such as codger and geezer are only mildly offensive whereas those for elderly

women such as crone and hag are distinctly offensive (Schulz 1975). Our language, like our society, is sexist.

Many scholars of sociology, philosophy, and feminist studies, including Judith Butler,

Erving Goffman, Michel Foucault, Jürgen Habermas, Anthony Giddens, and Howard Becker have included the consideration of language, discourse, and vocabularies in their theories.

Goffman and Becker focus on language as an essential part of everyday interaction and communication through symbols. Goffman acknowledges language and verbal communication, but is primarily concerned with non-verbal communication (e.g., Goffman 1959, 1967).

Goffman‟s work on frame analysis pays particular attention to the power of language and how it affects interactions between two or more people (Goffman 1974). In his work on labeling theory,

Becker argues that words and labels affect the social reality and identity of people (Becker 1963).

Language and its use are also widely studied in social constructionist theory. The strong version of the Sapir-Whorf hypothesis-- that language determines how the world is perceived-- is mostly dead (Bakker 2011). However, the weak version-- that language influences the social reality of its users-- is widely reiterated in different forms. Berger and Luckmann (1966 cited by

Pfohl 2008) suggest that language is what makes humans human and gives rise to social construction, i.e. that language allows humans to give objects meaning and thus create “reality” from those meanings. What is important about the relationship between language and social structure is that it is reciprocal. Per its very definition, social structure does not easily change.

However, language is ever-changing and evolving. The coining of new words (e.g., the hundreds of words coined by Shakespeare) and the shift in conventional grammar (e.g., from universal

“he” to the plural “they”) can change the way people perceive society and social reality. Lorber

(2008) cites the example of Swiss psychologist Julia Nentwich‟s efforts to employ alternative

language to combat the wide use of sexist language and thus alter social reality. One example of this effort was the use of gender neutral occupational titles (e.g., fire fighter instead of fireman, flight attendant instead of stewardess).

Evidence of sexism and patriarchy has been found by scholars in the terms used for our bodies (e.g., Ernster 1975; Gartrell and Mosbacher 1984; Spender 1985; Cameron 1992; Braun and Kitzinger 2001). Shilling uses the term “privileged body” to refer to the fact that men‟s bodies are often seen as the default and women‟s bodies are seen as inferior (2003:53), illustrated by examples such as the comparison of women‟s bodies (as deviant) in relation to men‟s bodies in the seminal anatomy text Grey’s Anatomy (Petersen 1998), or the treatment of pregnancy as a disorder (Rothman 2007). Similarly, Connell discusses the “negation” of the body, by which he means the tendency to focus on the small differences while ignoring the vast similarities between male and female bodies (Connell 1983, 1987 cited by Shilling 2003: 95). This focus on the small differences is easily seen in the plethora of terms for the one place the sexes are seen to differ most: the genitals.

Scholars in psychology, sociology, and linguistics have argued that slang terms for the genitals have a deleterious effect by promoting and maintaining heteronormative, androcentric views of sexuality and gender (e.g., Kutner and Brogan 1974; Gartrell and Mosbacher 1984;

Cameron 1992). Just as Schulz (1975) found for words referencing a specific gender, terms for the genitals are more likely to be negative when referring to the female body compared to the male body (Cameron 1992; Grossman and Tucker 1997; Braun and Kitzinger 2001). According to Gartrell and Mosbacher, “[girls] who were taught to call their genitalia „shame‟ or „nasty‟ could only assume that female genitalia were imbued with evil qualities” (1984: 874). Though there are more derogatory slang terms for females‟ genitals and they are more often sexual, men

and women reported using fewer slang terms for women‟s bodies than men‟s bodies (Grossman and Tucker 1997). This greater negativity, but less frequent use, may be due to the emotional weight these slang terms carry compared to those for men (Grossman and Tucker 1997).

Stereotypes of masculine aggression and feminine submission are evident in slang terms for the genitals as well (e.g., Genghis Khan compared to spunk bin) (Cameron 1992; Braun and

Kitzinger 2001).

The genitals, as well as all taboo subjects, are subject to both euphemism and dysphemism (e.g., Foote and Woodward 1973). Euphemism serves to civilize the body by hiding its natural but vulgar functions (Elias 1978a [1939], 1982 [1939] cited by Shilling

2003:131). By euphemizing the genitals human sexuality is obfuscated. Historically the female body, and specifically the female genitals, have been mystified and symbolically euphemized

(Greer 1971; Spender 1985). This obfuscation and mystification can cause women and men to fear the vulva and avoid earnest and candid discussion regarding sex(uality) (Gartrell and

Mosbacher 1984; Braun and Kitzinger 2001).

There is a tendency for both men and women to personify their sexual body parts (Braun and Kitzinger 2001; Cameron 1992; Cornog 1986; Naugler 2009; Gartrell and Mosbacher 1984).

The types of names given to body parts are either variants of the name of the person to which they belong or another name altogether (Cornog 1986). Personifications of male genitals are produced significantly more often than female genitals by both men and women (Braun and

Kitzinger 2001). The names given to male genitalia are often people of authority and fame

(Cameron 1992), but these types of names are not given to female genitalia by either males or females (Braun and Kitzinger 2001).

Often the act of personification is seen to represent the separation of oneself from the body part (objectification), and sometimes involves giving it a personality of its own (Cornog

1986; Cameron 1992; Bordo 1999; Braun and Kitzinger 2001; Potts 2001). Though the idea of a body part with a mind of its own has been a trope in literature and the media (e.g., zombies,

Thing from the Addams Family, “Wicked Willie” (referenced by Cameron 1992)), this concept is particularly true of the penis. However, the act of personification, especially of male genitalia, may have deleterious effects on a person‟s relationship with their own sexuality. Though

Cornog (1986) suggests the act may be benign in nature, other authors feel personification of genitalia may be more harmful to its users and society as a whole (e.g., Cameron 1992; Potts

2001). Cameron (1992) suggests that this Cartesian mind-body (or in this case mind-penis) split2 can be used as an excuse for a man‟s detrimental, or even illegal, sexual behavior. Cameron

(1992) alludes to a potentially compounding effect caused by the fact that many slang terms for the penis and sex refer to men as the aggressor, conqueror, and king. Potts (2001) sees personification as an alibi for the alleged inability of men to maintain self-control, to think rationally, and to be accountable for their actions. In addition, Potts (2001) argues that this alienation of one‟s sexuality restricts men‟s sexual experiences and inhibits them from being a responsible party during sexual encounters. The history of Western culture shows a reversal of which sex is considered insatiable and animalistic in their sexual instincts. During medieval times, women were thought to be “hot-blooded” and “sexually insatiable,” not men (Bordo

1999:245). The idea of men as relating to culture and women to nature is also explored in feminist research (e.g., Ortner 1972). In modern times, however, there is a stereotype of the animalistic male who, once aroused, is overtaken by his lust and “instinct” (e.g., Bordo 1999; see

also rape-myth acceptance scales by Muehleuhard and Felts 1998 and Payne, Lonsway, and

Fitzgerald 1999).

In their overview of gender and sociolinguistics, Thorne and Henley (1975) find that women are more likely to use euphemisms and proper grammar, and men are more direct and more likely to use swear words (Thorne and Henley 1975; Lakoff 1990). Similarly, in research on genital slang, gender differences were found in the reported knowledge of slang terms (Foote and Woodward 1973; Kutner and Brogan 1974; Cameron 1992; Braun and Kitzinger 2001), the nature of the slang terms (Kutner and Brogan 1974; Gartrell and Mosbacher 1984; Cameron

1992; Grossman and Tucker 1997; Naugler 2009), and even how slang terms are perceived

(Wells 1990). Men tend to use more male-dominance-related slang for coitus (e.g., fuck) than women used (e.g., making love), especially those males who have traditional sex-role views

(Kutner and Brogan 1974). However, females produced slang terms for male genitalia that tended to reject the dominant discourse produced by men (Cameron 1992). For example, women produced slang terms for the penis such as Thomas, Ralph, Peter-dinkie, pole, and pencil whereas men produced His Excellency, hammer of the gods, Genghis Khan, jackhammer, and rectum wrecker (Cameron 1992). Girls use more euphemistic and pejorative terms for their own genitals than boys did for theirs (Gartrell and Mosbacher 1984). Though virtually all demographic characteristics impact speech styles (Thorne and Henley 1975), no studies consider race or socio-economic status, and only one –from two decades ago– investigates differences in slang terms by sexual orientation (Wells 1990).

Research and theories regarding language were plentiful a few decades ago. Many second-wave feminists emphasized the impact of words and language. The field of sociolinguistics produced much research, complementing the prominence of language in

symbolic interactionist theories. However, the interest in language has apparently waned in recent years, leaving the progress of the language-related literature in sociology stalled. It is unclear why research on this topic has declined, but it seems unfortunate and unwarranted given the many fascinating potential research questions left unexplored.

Though ample research has been done regarding genital slang and other taboo words, the literature contains many omissions and limitations. Much of the research on genital slang fails to consider demographic characteristics beyond gender and age. Other, potentially important, variables such as sexual orientation, education, race, and socioeconomic status (SES) are largely missing from the literature. Furthermore, although research on genital slang includes measures of knowledge of slang, use of slang, and perceived offensiveness of slang, few studies include all three measures. This study includes previously ignored demographic variables and explores their impact on slang knowledge, use, and perceived offensiveness. Many scholars discuss the potentially deleterious effects slang (especially euphemistic, dysphemistic, abject, dangerous, and authority-related terms) can have on a person‟s relationship with his/her own sexuality

(Cameron 1992; Braun and Kitzinger 2001). However, no studies empirically address this hypothesis. Using quantitative data and sexism scales, this paper seeks to address this question.

Additionally, I use demographic variables as control variables to explore connections between slang and sexism. In sum, this study provides updated information on slang usage, addresses gaps in the literature regarding demographic characteristics, the relationship of demographic characteristics to slang and sexism, and explores the much-discussed hypothesis of a connection between genital slang and sexism.

Hypotheses

There is evidence of both slang and sexism varying by demographic characteristics. To assess any correlation between sexism and slang, I needed to control for demographic characteristics to avoid spurious relations. The model has four hypotheses: (1) demographic characteristics will have significant effects on slang knowledge, use, offensiveness, and categories; (2) demographic characteristics will have significant effects on sexism; (3) slang knowledge, use, offensiveness, and categories will be significantly correlated with sexism; (4) slang knowledge, use, offensiveness, and categories will be significantly correlated with sexism while controlling for demographic characteristics. Regressions are calculated for hypotheses (1) and (2) because demographic characteristics cannot be caused by slang or sexism. Because it is nearly impossible to determine the causal order between slang and sexism, only correlations are calculated in the analysis for hypotheses (3) and (4).

Methods

Data were collected from January to June of 2011 from 194 respondents to an IRB- approved survey. The respondents were primarily undergraduate students, all of whom attended the University of Cincinnati.

Participants were recruited in undergraduate sociology classes at the university; the survey was administered during class time. The professor and any teaching assistants were asked to leave for the entire duration of the survey. Consent was indicated by completion of the survey. Respondents were required to be native English speakers and 18 years of age or older.

(Questions asking specifically about native English speaker status and age were used to determine if the respondents qualified for participation.) Because some students were in multiple

sociology classes and the research spanned two academic quarters, potential participants were asked not to participate more than once. Any surveys found to be incomplete or containing replies indicating non-native English speaker status or minor status were shredded and not entered into the dataset. The survey took an average of 25 minutes to complete and consisted of three sections: demographic questions, an assessment of genital slang knowledge, use, and perceived offensiveness, and sexism scales.

In the first section of the survey, demographic information was collected regarding race

(1 = White or Caucasian, 2 = Black or African American, 3 = American Indian, Eskimo, or Aleut,

4 = Asian (including Asian Indian), 5 = Pacific Islander, 6 = Middle Eastern, Arab, Turkish, or

Persian, 9 = other), sex, sexual orientation (1 = heterosexual or straight, 2 = bisexual, 3 = lesbian, gay, or homosexual, 8 = don‟t know, 9 = other), age, highest educational degree attained, years in school, number of parents in the home prior to graduation from high school, parental education, parental occupation, parental income, current religious affiliation, and religion the respondent was raised in. Highest educational degree attained was measured as an ordinal variable with 1 = some high school, 2 = GED, 3 = high school diploma, 4 = associate/junior college (e.g., AA), 5 = bachelor‟s degree (e.g., BA, BS), 6 = master‟s degree (e.g., MA, MS), 7 =

PhD, and 8 = professional degree (e.g., DDS, JD, MD). Similarly, parent‟s educational attainment was measured as 1 = none, 2 = some high school, 3 = GED, 4 = high school diploma,

5 = associate/junior college, 6 = bachelor‟s degree, 7 = master‟s degree, 8 = PhD, and 9 = professional degree.

The second section assessed knowledge, use, and perceived offensiveness of genital slang terms. The section was divided into two parts, one for the male genitals and one for the female genitals. Participants were asked to use 1.5 minutes to list as many non-medical English terms

for the genitals as they could think of in the provided blank spaces. These terms could be for the genitals as a whole or for individual parts. A timer was used, and a 30 second warning was given to the entire classroom. The time limit was implemented both to discourage spontaneous slang creation and to assess the most salient terms in the respondent‟s vocabulary. After the 1.5 minutes expired, respondents rated on an 8-point Likert scale ranging from 0 (never) to 7 (very frequently) how often they used the slang terms and how offensive on a 7-point Likert scale ranging from 1 (not at all offensive) to 7 (extremely offensive) they personally found the slang terms. Because many genital terms double as insults (e.g., pussy, dick), most respondents were instructed that “use” of the terms meant their use in reference to the genitals, not to individuals.

This procedure was the same for both male genital terms and female genital terms.

The third section of the survey contained three modified versions of sexism scales created by different scholars. The scales used were the Ambivalent Sexism Inventory (Glick and Fiske

1997), the Sexual Beliefs Scale (Muehleuhard and Felts 1998), and the Modern Sexism Scale

(Swim et al. 1995). These scales were chosen for their broad coverage of sexism with minimal overlap, contemporary relevance (unlike, for example, the outdated Attitudes Toward Women scale of Spence and Hahn 1997), and their established use in previous research. The three scales were edited to remove potentially problematic wording (e.g., double-barreled statements) and standardize references to men and women to be consistent (instead of guys and girls, boys and girls, etc.). Each scale was preceded by a short instructional paragraph to clarify the reference frame of the statements in the scales (e.g., “The Sexual Beliefs Scale assesses attitudes regarding relationships between men and women in general and not personal preferences”). Each statement was followed by a 7-point Likert scale for respondents to indicate their level of agreement or disagreement, ranging from 1 (disagree strongly) to 7 (agree strongly).

Data from completed surveys were entered into SPSS for analysis. Additional variables were created using the given data. For example, if the number of years the respondent had been in college subtracted from the respondent‟s age was between 17 and 19, they were coded as a

“traditional student” using a dummy variable (0 = non-traditional, 1 = traditional). Other dummy variables, such as sexual orientation (0 = non-straight, 1 = straight) and white (0 = non-white, 1 = white), were created as well. Parental occupational prestige was measured using nominal occupational categories: 1 = professional, technical or similar worker, 2 = manager or administrator, except on a farm, 3 = sales, clerical, or similar worker, 4 = craftsmen, farm owner, farm manager, or similar worker, 5 = operative or similar worker, 6 = service worker, 7 = laborer, farm, or similar worker, 8 = not in labor force, 9 = don‟t know, and a space was provided for respondents to specify. Using the 1980 census codes and the 1989 occupational prestige scores

(National Opinion Research Center 2011), data from the GSS were used to find the average prestige score for each occupational category weighted by the number of respondents in the GSS with a particular occupation. The resulting scores were as follows: professional, technical or similar worker = 63, manager or administrator, except on a farm = 53, sales, clerical, or similar worker = 40, craftsmen, farm owner, farm manager, or similar worker = 41, operative or similar worker = 33, service worker = 34, laborer, farm, or similar worker = 28, not in labor force = 34.

The score of 34 was given to those not in the labor force based on the findings of Dworkin

(1981) that stay-at-home mothers have an occupational prestige score similar to that of service workers. Since the vast majority (98.3%) of respondents had a mother or other female parental figure present in their household before graduating from high school, I felt this to be the best solution. None of the respondents listed parent #1 as their father and unemployed.

For both male and female genital terms, variables for average use and average offensiveness were created. Because these variables include non-slang terms, special attention was used to refer to them as measuring average use or average offensiveness of genital terms (as opposed to genital slang terms). Additionally, a variable measuring the variance of offensiveness values was created because response set was suspected (e.g., responding “not at all offensive” to any and all terms listed), especially for male genital terms. This may be due to male respondents denying being offended by such terms. Last, an interaction term of use and offensiveness was created. The interaction term is the product of the use and offensiveness responses on the Likert scales. Its values range from 0 to 49. For example, a respondent indicating 2 = rarely for use of a genital term and 7 = extremely offensive for the same genital term would have a value of 7 x 2 = 14 for the use-offensiveness interaction term. The higher the value on the interaction term, the more the respondent uses the term while simultaneously finding it more offensive. When entering the data I noticed some respondents indicated using a term often, but personally finding it highly offensive. This surprising result caught my attention as something worth investigating using the interaction term mentioned above. (See Appendices

A and B for all terms listed and their frequency).

Respondent‟s slang terms were analyzed for terms that (1) framed the genitals as dangerous (e.g., “The Trap”) or sex as an act of violence (e.g., “Hymen Hammer”), (2) evoked images of authority or fame (e.g., “Prince”), (3) related to abjection and filth (e.g., “Blood Box”), terms that were (4) euphemisms (e.g., “Down There”) and (5) nonsense (e.g., “Hootchie-Coo”).

Euphemisms were separated from nonsense terms but a combination variable called euphemism+nonsense was created because nonsense terms can have the same effect of obfuscating or sanitizing the true meaning just as euphemisms do. The spelling of the terms was

standardized for consistency and I used my best judgment to determine if a spelling variant qualified as a unique term. The number of terms that fell into each category was recorded, as well as what percent those categorized terms comprised of all slang terms the respondent listed, the average use, and average offensiveness of the categorized terms. (See Appendices C and D for all terms in each category).

The five categories mentioned above were chosen based on the findings of previous studies on genital slang (e.g., Gartrell and Mosbacher 1984; Cameron 1992; Braun and Kitzinger

2001). The first three categories relate to the patriarchal framing of the body and sexual intercourse as male-dominant. The latter two categories obfuscate the body and sex, which scholars (e.g., Gartrell and Mosbacher 1984; Braun and Kitzinger 2001), as mentioned before, suggest can have a deleterious effect on an individual‟s view of gender and sexual activity.

Finally, because the term was commonly listed and frequently considered extremely offensive, a dummy variable for the existence of the word “cunt” was created. Colleagues cited anecdotal evidence that suggested that the casual use or the lack of perceived offensiveness of this particular word may be correlated with sexist attitudes and beliefs.

Due to large proportions of non-response, lack of knowledge, and/or unclear answers, parental income and all religion-related items were removed from the final dataset. For example,

20.6% of respondents did not know their parent‟s approximate income at the time they graduated high school. Many respondents provided confusing or incomplete responses to the religion questions (e.g., “Catholic Protestants”). The survey asked respondents to indicate the adults in their home during their childhood, and 6.3% indicated more than two parents. This, in addition to the poor wording and ordering of the question, resulted in only the first adult listed being in the final dataset. In 98.3% of the cases, the mother or other female parental figure was this adult.

In cases where no female parental figure was listed, the male parental figure was used. The occupational prestige scores from 1989 may not be accurate today, but they provide a rough estimate of occupational prestige. However, because parental income was not included in the final dataset, I felt it important to have more than just parental education as a measure of SES, even though it may be a rough measure. Lastly, the state or country where the respondent spent the majority of their childhood was asked but not used in the final dataset.

Benefits and Limitations of Using Surveys

The choice of survey research over other methods was two-fold. First, a set of detailed quantitative data could be assembled for analysis to test statistical significance of the hypotheses.

Second, the anonymous nature of the survey allows for more candid responses, especially to items pertaining to genital slang use and sexist beliefs and attitudes. Interviewing people on this topic could lead to embarrassment and would probably result in fewer slang terms being offered by participants. This method does have its limitations. For example, nonsensical or confusing responses to items (e.g., incongruent religion and denominations) could not be verified or clarified due to the anonymous nature of the responses. There was also some evidence in the form of comments on the surveys that respondents felt the survey constrained responses or was unclear. For example, one respondent wrote “poor wording” next to an item on a sexism scale.

Another student wrote “hell yes!” next to a few items on a sexism scale, exemplifying the limitations of Likert scales to measure degrees of commitment to a response. Lastly, as with any non-random sample research, the findings of this study are not generalizable to the population as a whole. Any findings should be considered with the sample‟s demographic characteristics and geographical location in mind.

FINDINGS

Demographics

Of the 194 original respondents, 19 surveys contained missing data and were removed through listwise deletion. As seen in Table 1, the remaining 175 respondents were 61% female with a mean age of 20.9 years old3. These respondents were 83% white, 10% black, and 7%

“other”. No respondents indicated they were Hispanic. 94.29% identified their sexual orientation as straight. Regarding the educational attainment of the respondents, 1.71% had earned a GED, 88% had earned a high school diploma, 6.29% had earned an associate‟s or junior‟s degree, and 4% had earned a bachelor‟s degree. The average time spent working toward their current degree was 2.46 years. 90% of the respondents were traditional students, i.e., that they started college between ages 17 and 19. The average education of parent #1 (most frequently the mother) was a bachelor‟s degree, but 33.71% attained only a high school diploma,

15.43% attained an associate‟s or junior‟s degree, 30.86% attained a bachelor‟s degree, and

12.57% attained a master‟s degree. The average occupational prestige score of parent #1 (again, usually the mother), was 49.02 based on the 1989 scores.

The 19 respondents who were removed from the final dataset did significantly differ from the remaining 175 on a few measures. These 19 respondents were more likely to be black (N =

7), to list more words for the male genitals (but not necessarily more actual slang terms), to list more words and more actual slang terms for the female genitals, and have higher scores on the

Complementary Gender Differentiation and Protective Paternalism subscales. Thus, using the N

= 175 dataset, blacks, the number of male genital terms listed, the number of female genital

terms listed, the number of actual female genital slang term, and scores on the Complementary

Gender Differentiation and Protective Paternalism subscales will all be underestimated.

Table 1: Descriptive Statistics of Demographic Variables (N = 175) Standard Mean Deviation Variance Minimum Maximum Sex (1 = male) 0.39 0.49 0.24 0.00 1.00 Age 20.90 3.68 13.58 18.00 47.00 Straight* 0.94 0.23 0.05 0.00 1.00 White* 0.83 0.38 0.14 0.00 1.00 Black* 0.10 0.30 0.09 0.00 1.00 Other Race* 0.07 0.25 0.06 0.00 1.00 Education 3.13 0.47 0.23 2.00 5.00 Years In School 2.46 1.35 1.82 1.00 5.00 Traditional Student* 0.90 0.30 0.09 0.00 1.00 Parent #1's Education 5.16 1.38 1.91 1.00 9.00 Parent #1's Occupational Prestige 49.02 12.93 167.19 28.00 72.00

Frequency Percent Education Some High School or Less 0 0.00% GED 3 1.71% High School Diploma 154 88.00% Associate/Junior's Degree 11 6.29% Bachelor's Degree 7 4.00% Master's Degree 0 0.00% PhD 0 0.00% Professional Degree 0 0.00% Other 0 0.00% Adult #1's Education

None 1 0.57% Some High School or Less 6 3.43% GED 2 1.14% High School Diploma 59 33.71% Associate/Junior's Degree 27 15.43% Bachelor's Degree 54 30.86% Master's Degree 22 12.57% PhD 1 0.57% Professional Degree 3 1.71% Other 0 0.00% * Dummy variables where 1 equals membership in given status

Slang

Male Genital Terms

Table 2 shows descriptive statistics for variables related to male genital terms. On average, about 7.5 terms were listed as male genital slang by participants, but about only 7 of those terms were actual slang terms. The other terms were deemed to be non-slang terms

(discussed in depth later). The average use of all the terms listed by participants was 2.464, which is between “rarely” and “infrequently.” The Likert scale values for use ranged from “0 = never” to “7 = very frequently.” The average perceived offensiveness (recall that this is how offensive the respondent personally finds the corresponding listed term) was 1.8 which is between “not at all offensive” and “slightly offensive.” The Likert scale values for offensiveness ranged from “1 = not at all offensive” to “7 = extremely offensive.” The variance of offensiveness was 1.1. The average value of the use-offensiveness interaction variable was 4.2.

That is to say, the average of the use value multiplied by the offensiveness value for each term was approximately 4. This value could be obtained by replying “2 = rarely” for use and “2 = slightly offensive” for all terms listed. The higher the use-offensiveness interaction value, the more the terms are used while the respondent simultaneously finds them more offensive. An average value of 4 does not indicate an exceptionally high level of simultaneous high use and high offensiveness.

Table 2: Descriptive Statistics of Variables Measuring Male Genital Terms (N = 175) Mean Standard Deviation # of Male Genital Terms Listed 7.509 3.019 # of Male Genital Slang Terms 7.046 3.024 Average Use 2.464 1.111 Average Offensiveness 1.759 0.901 Average Variance of Offensiveness* 1.122 1.649 Average Use x Offensiveness 4.227 2.970 Danger Category

Number 0.160 0.488 Percent 2.000% 5.910% Average Use 0.062 0.383 Average Offensiveness 0.273 0.843 Authority Category

Number 0.057 0.256 Percent 1.173% 8.106% Average Use 0.069 0.475 Average Offensiveness 0.077 0.357 Abject Category

Number 0.240 0.502 Percent 2.792% 5.864% Average Use 0.560 1.384 Average Offensiveness 0.260 0.589 Euphemism Category

Number 0.297 0.590 Percent 4.275% 9.308% Average Use 0.429 1.144 Average Offensiveness 0.351 0.768 Nonsense Category

Number 0.343 0.604 Percent 4.877% 8.746% Average Use 0.398 1.058 Average Offensiveness 0.467 0.966 Euphemism and Nonsense Category

Number 0.640 0.803 Percent 9.153% 11.741% Average Use 0.827 1.521 Average Offensiveness 0.819 1.322 * N = 174

A total of 244 unique terms were listed by respondents as slang terms for the male genitals (see Appendix A). Of these 244, only 233 were deemed slang terms referring to the male genitals. The other 11 terms ranged from medical terms (e.g., penis, testicles), quasi- medical terms which could be used as either slang or medical terms (e.g., shaft, head), and terms not relating to the male genitals (e.g., “taint” which typically refers to the perineum, “numb nuts”4 which typically refers to a foolish individual). The ten most commonly listed terms for the male genitals were dick (N = 161), balls (N = 134), cock (N = 93), wiener (N = 60), nuts (N

= 54), sack (N = 38), junk (N = 34), Johnson (N = 30), schlong (N = 26), package (N = 19), and

Peter (N = 19).

Table 2 also shows descriptive statistics for the male genital terms in the six analytic categories (danger, authority, abject, euphemism, nonsense, and euphemism+nonsense). The average number of danger terms for the male genitals listed by respondents was 0.16, and on average those danger terms comprised 2% of the total actual slang terms listed. The average use of these danger terms among all respondents was 0.062 which is between “0 = never” and “1 = very rarely” and the average offensiveness of these danger terms was 0.27 which is between “1 = not at all offensive” and “2 = slightly offensive”. This category contained 15 unique terms, such as “hymen hammer,” “peach cleaver,” and “rocket.”

The average number of authority terms listed by all respondents was 0.06 and those terms comprised, on average, 1.17% of the total actual slang terms listed. This category contained 9 unique terms, such as “King and his Jewels” and “Big Daddy.” The average use of terms in this category by all 175 respondents was 0.07 and the average offensiveness was 0.08.

The abject category contained 6 unique terms, such as “junk” and “fools.” The average number of terms that fell into the abject category was 0.24 and on average they comprised 2.8% of all actual slang terms listed by respondents. The average use of these terms by all respondents was 0.56 and the average offensiveness was 0.26.

The average number of terms listed that were categorized as euphemisms was 0.30 terms and the average percent of the total listed slang terms these euphemisms comprised was 4.3% on average. The average use of these terms by all respondents was 0.43 and the average offensiveness was 0.35. This category contained 13 unique terms, including “crotch,” “no-no parts,” and “special place.”

Last, the nonsense category contained 11 unique terms, which included “ding dong,”

“tallywacker,” and “wang.” The average number of nonsense terms listed by respondents was

0.34 and they comprised an average of 4.9% of all male genital slang listed. The average use of terms in this category was 0.40 and the average offensiveness was 0.47. The descriptive statistics for the euphemism+nonsense category are the sum of the two separate categories (see

Table 2).

(See Appendix C for all male genital slang listed for each category and Appendix A for all male genital terms listed by respondents).

Female Genital Terms

Table 3 shows descriptive statistics for variables related to female genital terms (see

Appendix B for all female genital terms listed). The average number of terms listed for the female genitals was 6.1 terms and on average 5.5 terms were slang terms. The average use of all the terms listed as 1.97, which is between “1 = very rarely” and “2 = rarely.” The average

perceived offensiveness of all the terms listed was 2.66 which is between “2 = slightly offensive” and “3 = mildly offensive.” The average variance of offensiveness for all listed terms was 2.78 and the average value of the use-offensiveness interaction variable was 4.31. Again, a value of 4 could result when the value of use for a term was “1 = very rarely” and the value of offensiveness for a term was “4 = somewhat offensive.” An average value of 4 is not exceptionally large given that the highest possible value is 7 x 7 = 49 (meaning the terms are used all the time and considered extremely offensive by the user).

There were a total of 268 unique terms were listed by respondents as female genital slang.

Of these, only 236 were deemed actual genital slang. The other 32 terms included terms for the breasts (e.g., boobs, chesticles, tatas), medical terms (e.g., clitoris, womb), and terms not referring to the female genitals (e.g., pork steeple, ass). Though listed often (N = 28), the term

“lips” was deemed more medical than slang and not included in the slang terms list. The ten most common slang terms listed by respondents were pussy (N = 148), cunt (N = 106), vag/vaj/vadge (N = 64), va-jay-jay (N = 63), clit (N = 40), twat (N = 34), snatch (N = 27), cooter

(N = 20), cooch (N = 16), and box (N = 15).

Table 3 also shows descriptive statistics for female genital slang that fell into the aforementioned categories. The table also shows information regarding the use of the term

“cunt.” The danger category contained 15 unique terms, including “black hole,” “gash,” and

“man stealer.” The average number of terms listed by all participants that fell into this category was 0.12 and these danger terms on average comprised 2.3% of the actual slang terms listed by participants. The average use of these terms was 0.11, which is between “0 = never” and “1 = very rarely.” The average offensiveness of these terms was 0.32, which is below “1 = not at all offensive.”

Table 3: Descriptive Statistics of Variables Measuring Female Genital Terms (N = 175) Standard Mean Deviation # of Female Genital Terms Listed 6.091 2.829 # of Female Genital Slang Terms 5.491 2.500 Average Use 1.968 1.232 Average Offensiveness 2.662 1.406 Variance of Offensiveness* 2.782 2.551 Average Use x Offensiveness 4.312 4.181

Danger Category

Number 0.120 0.359 Percent 2.301% 9.262% Average Use 0.114 0.563 Average Offensiveness 0.320 1.184

Authority Category

Number 0.006 0.076 Percent 0.114% 1.512% Average Use 0.000 0.000 Average Offensiveness 0.006 0.076

Abject Category

Number 0.131 0.355 Percent 1.927% 5.613% Average Use 0.171 0.805 Average Offensiveness 0.366 1.186 Euphemism Category

Number 0.217 0.513 Percent 3.669% 9.105% Average Use 0.437 1.305 Average Offensiveness 0.237 0.608 Nonsense Category

Number 0.823 0.987 Percent 15.066% 18.221% Average Use 1.308 1.896 Average Offensiveness 0.912 1.200

Euphemism and Nonsense Category

Number 1.040 1.131 Percent 18.735% 19.533% Average Use 1.745 2.433 Average Offensiveness 1.149 1.361 Cunt Category

Percent of R's who Listed Term 60.000% 49.130% Average Use 0.857 1.469 Average Offensiveness 3.086 3.045 * N = 170

Only 1 term listed by one person, “Clint,” was listed for female genital slang that was categorized as authority. This could be a misspelling of the slang term “clit” or could be a reference to the male name made most famous by Clint Eastwood. Because one-time anonymous survey research does not allow the researcher to ask for clarification on responses, I took the response as intending to be the male name. The respondent indicated “0 = never” for use of this term, so no regressions or correlations were possible with the average use of authority for female genital terms. The respondent found this term “not at all offensive.” Whether the term was indeed an authority term or a misspelling, it this individual had no variance to create any significant correlations.

The abject category had a total of 17 unique terms, such as “ass preview,” “stinker,” and

“waste basket.” The average number of slang terms listed by respondents that fell into this category was 0.13, which on average comprised of 1.93% of the total slang terms listed by respondents. The average use by all respondents of abject terms was 0.17 and the average offensiveness was 0.37.

A total of 19 unique terms were categorized as euphemisms. These terms included “her,”

“love below,” and “soft place.” The average number of slang terms listed by respondents that were categorized as euphemistic was 0.22 and the average percentage of slang terms listed by respondents that fell into this category was 3.67%. The average use by all participants of euphemistic terms was 0.44 and the average offensiveness of these terms by all participants was

0.24.

The nonsense category contained a staggering 30 unique terms for the female genitals.

These terms included “coslopus,” “hoo-hah,” “kooka,” the widely used “va-jay-jay,” and

“whispering eye.” The average number of slang terms listed by respondents that were nonsense terms was 0.82 and on average these terms comprised 15% of the actual slang terms listed by respondents. The average use of nonsense terms by all respondents was 1.31 which is between

“1 = very rarely” and “2 = rarely.” The average offensiveness of nonsense terms by all respondents was 0.92.

Last, 60% of all respondents listed the term “cunt” as a female genital slang term. This term was the second most common term listed by respondents. The average use of this term by all respondents was 0.86, which is between “0 = never” and “1 = very rarely.” The average offensiveness of this term by all respondents was 3.1, which is between “3 = mildly offensive” and “4 = somewhat offensive.”

(See Appendix D for all female genital slang listed for each category and Appendix B for all female genital terms listed by respondents).

Sexism

Using Pett, Lackey, and Sullivan (2003), Aneshensel (2002), and DeVellis (2003) as guides, each of the modified scales were analyzed for factors and reliability. The authors of the

Ambivalent Sexism Inventory suggest two subscales: Hostile Sexism and Benevolent Sexism

(Glick and Fiske 1997). Within the Benevolent Sexism subscale, the authors mention three factors which they call “Heterosexual Intimacy,” “Protective Paternalism,” and “Complementary

Gender Differentiation.” When a factor analysis was performed on all 22 items, items 17 (“A good woman should be set on a pedestal by her man.”) and 18 (““Few women get a kick out of teasing men by seeming sexually available and then refusing male advances.”) did not load sufficiently (< 0.3) on any factor and were subsequently removed from the scale. The remaining

20 items produced five factors, four of which were the factors suggested by the original authors

(Glick and Fiske 1997). The fifth factor was two items regarding feminism which were originally placed in the hostile sexism factor by the authors. These items loaded on their own separate factor, which I call “Anti-Feminism.” I suspect this additional factor is due to the sample being taken from sociology classes where feminist theory is taught and used and thus students were less likely to be anti-feminist.

The items in the Hostile Sexism factor primarily refer to stereotypes about women (e.g., women will keep a man on a tight leash, women cry sexism when they lose a fair competition, etc.). The two items in the Anti-Feminism factor measure beliefs that feminists are demanding special favors in the guise of equal treatment. Heterosexual Intimacy measures the belief that men and women “need” each other to be “complete”. Protective Paternalism measures the idea that women need protection and should be cherished. Lastly, Complementary Gender

Differentiation contains items referring to “positive” attitudes toward women such as “women have refined tastes” and “women have superior moral sensibilities.”

Table 4 shows descriptive statistics for all of the scales used and Table 5 shows the reliability coefficients for the Ambivalent Sexism Inventory. The means, standard deviations, and alpha coefficients were as follows: Hostile Sexism has mean of 3.808, standard deviation of

1.186, and α = 0.871, Anti-Feminism has mean of 3.920, standard deviation of 1.396, and α =

0.643, Protective Paternalism has mean of 3.680, standard deviation of 1.375, and α = 0.582,

Complementary Gender Differentiation has mean of 4.484, standard deviation of 1.191, and α =

0.751, and Heterosexual Intimacy has mean of 3.461, standard deviation of 1.266, and α = 0.649.

For all of the factors except the Complementary Gender Differentiation factor, the average response to items in the factors was between 3 and 4, which corresponds to answering between

“3 = disagree somewhat” and “4 = neither agree nor disagree.” On these four factors, roughly

68% of the respondents answered within “2 = disagree” and “5 = agree somewhat.” The average response to items in the Complementary Gender Differentiation factor was between “4 = neither agree nor disagree” and “5 = agree somewhat.”

Table 4: Descriptive Statistics of the Sexism Scale Subscales (N = 175) Standard Mean Deviation Ambivalent Sexism Inventory Hostile Sexism 3.808 1.186 Anti-Feminism 3.920 1.396 Heterosexual Intimacy 3.680 1.375 Protective Paternalism 4.484 1.191 Complementary Gender Differentiation 3.461 1.266 Modern Sexism Scale

Against „Special Treatment‟ 3.291 1.104 Equality Attained 3.230 0.977 Sexual Beliefs Scale

Token Resistance 2.990 1.230 Leading On Justifies Force 1.727 0.988 Women Life Force 4.009 1.273 Men Should Dominate 3.193 1.250 No Means Stop 6.783 0.441

Roughly 68% of respondents answered within “3 = disagree somewhat” and “6 = agree” on that factor. While the Cronbach‟s α values are not particularly high, they are passable with the consideration that these low levels of reliability will attenuate results and thus decrease statistical significance.

The Modern Sexism Scale is suggested to be unidimensional by its authors (Swim et al.

1995), but two factors were extracted. Judging by the wording of high-loading items (Pett et al.

2003), the two factors represent attitudes regarding “women‟s groups‟ anger” and the perceived attainment of gender equality. The former reflects perceived special treatment for women and

unwarranted demands by feminists and activists. I have decided to call the factors “Equality

Attained” and “Against „Special Treatment‟”. One item was found to cross-load. Table 5 shows the alpha values when the item was placed in either factor. There was a net gain in reliability when the item was placed in the equality attained factor. The resulting means, standard deviations, and alpha values were mean of 3.230, standard deviation of 0.977, and α = 0.808 for

Against Special Treatment and mean of 3.291, standard deviation of 1.104, and α = 0.647 for

Equality Attainted (see Tables 4 and 5). For both factors, the average response to items within the factors was between “3 = disagree somewhat” and “4 = neither agree nor disagree.” Roughly

68% of the respondents answered within “2 = disagree” and “5 = agree somewhat.” The α value for the Against „Special Treatment‟ factor is respectable, though the value for the Equality

Attained factor is on the low side. As with the Ambivalent Sexism Inventory factors, the attenuation effect of a low α must be taken into consideration.

The Sexual Beliefs Scale was created by Muehleuhard and Felts (1998) and is in essence a measure of rape-myth belief. The authors suggest five subscales relating to perceived attitudes of heterosexual sexual relations: Token Resistance, Leading On Justifies Force, Women Like

Force, Men Should Dominate, and No Means Stop. Token Resistance reflects the stereotype that women often say “no” to sexual advances to maintain an image of a proper woman when they in fact mean “yes”. Leading On Justifies Force contains items that measure the belief that if a woman leads a man on sexually, the man is justified in sexually forcing himself on her. Women

Like Force measures the stereotype that women are aroused when men use physical force on them. Men Should Dominate reflects the idea that men should dominate and control sexual encounters. Lastly, No Means Stop measures belief that when a woman says “no” during a

sexual encounter, it means “stop”. This particular factor is coded so that higher values indicate non-rape-myth adherence.

Initially four factors were extracted, but a high percentage of large residuals from the reproduced correlation matrix suggested five factors should be extracted. When five factors were extracted, they roughly fell into the five factors suggested by the authors. Two items were found to cross-load strongly. Table 5 shows the alpha values of the scales when the items were placed in the strongest loaded factor (“before”) and in their theoretically congruent factor

(“after”). Though the net alpha was decreased, the “after” factors were kept because the amount alpha decreased was minimal and the factors match the authors‟ original findings. The resulting means, standard deviations, and reliability coefficients are mean of 2.990, standard deviation of

1.230, and α = 0.77 for Token Resistance, mean of 1.727, standard deviation of 0.988, and α =

0.826 for Leading On Justifies Force, mean of 4.009, standard deviation of 1.273, and α = 0.864 for Women Like Force, mean of 3.193, standard deviation of 1.250, and α = 0.796 for Men

Should Dominate, and mean of 6.783, standard deviation of 0.441, and α = 0.673 for No Means

Stop (see Tables 4 and 5). The low level of alpha for No Means Stop is most likely due to a high mean value and subsequent low levels of variance in responses (see Table 4). All five of the factors have at least „minimally acceptable‟ (DeVellis 2003:95) Cronbach‟s α values.

Due to the exploratory nature of this research, the small sample size and underestimation of several items due to missing data removal, correlations and regressions were considered significant at p < 0.1 instead of the standard p < 0.05. Though some of the Cronbach‟s alpha values were lower than what is considered desirable (Pett et al. 2003), the factors were used with the understanding that regressions and correlations will be attenuated. The choice of p < 0.1 will help offset the effects of this attenuation.

Table 5: Number of Items and Cronbach's Alpha Coefficients for Extracted Sexism Scale Factors with Crossloaded Items Placed In Different Factors to Determine Changes in Alpha (N = 175) Initial Extraction Crossloaded Items Moved # of Items α # of Items α Δα Ambivalent Sexism Inventory Hostile Sexism 8 0.871 - - - Anti-Feminism 2 0.643 - - - Benevolent Sexism Hetero. Intimacy 4 0.694 - - - Protective Paternalism 3 0.582 - - - Comp. Gender Diff. 3 0.751 - - - Modern Sexism Scale Against 'Special Treatment' 5 0.810 4 0.808 -0.002 Equality Attainted 3 0.569 4 0.647 0.078 Sexual Beliefs Scale Token Resistance 3 0.734 4 0.770 0.036 Leading On Justifies Force 5 0.843 4 0.826 -0.017 Women Like Force 3 0.853 4 0.864 0.011 Men Should Dominate 5 0.833 4 0.796 -0.037 No Means Stop 4 0.673 4 0.673 0.000

With the use of p < 0.1, we expect to find significance approximately 1 out of 10 times by chance. The following four subsections will discuss which areas had greater concentrations of significant findings than would be expected by chance.

Hypothesis 1: Demographic characteristics have significant effects on slang knowledge, use, offensiveness, and categories.

Tables 6 and 7 show the unstandardized regression coefficients, significance levels, R2 values, adjusted R2 values, F-test values, and F-test significant levels when the slang-related variables (excluding the categories variables of danger, authority, abject, euphemism, nonsense, euphemism+nonsense, and “cunt”) were regressed on the demographic variables age, highest educational degree attained, years in school, parent #1‟s educational attainment, and parent #1‟s

occupational prestige score as well as the dichotomous variables sex/gender, straight, black, other race, and traditional student. A total of 17 coefficients were significant at the p < 0.1 level.

Male respondents list an average of 1.28 more male genital terms than female respondents, and they list an average of 1.43 more female genital slang terms than female respondents (see Table

6). However, there were no statistically significant differences between male and female respondents in the number of terms listed or slang terms listed for the female genitals (see Table

7). For every one year increase in age of a respondent, there was an average of a 0.06 unit increase in average use of male genital terms (see Table 6).

Respondents who identify as straight have 0.52 more units in average offensiveness for male genital terms than non-straight respondents (see Table 6). For every one level increase in educational attainment by a respondent, on average respondents list 0.84 more slang terms for the female genitals, have an increase of 0.44 units of average use of female genitals terms, and have a decrease of 0.43 units of average offensiveness of female genital terms (see Table 7). For every additional year in school a respondent experiences, there was an average increase of 0.39 terms listed for the male genitals and 0.47 slang terms listed for the male genitals (see Table 6).

Similarly, for every additional year in school, respondents on average list 0.36 more terms for the female genitals and 0.27 more slang terms for the female genitals (see Table 7). For every one point increase in parent #1‟s occupational prestige score, respondents on average list 0.04 terms for the male genitals and 0.04 slang terms for the male genitals (see Table 6). Race, status as a traditional student, and parent #1‟s educational attainment do not produce statistically significant differences.

Table 6: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Male Genital Term Variables Are Regressed on Demographic Variables (N = 175)1 # of Words # of Slang Avg. Use Avg. Off. Off Var.** Avg. Use*Off. Independent Variables b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. Constant 0.317 0.915 0.990 0.739 1.235 0.278 1.733 0.065 0.743 0.680 1.409 0.651 Sex (1 = male) 1.275 0.005 1.428 0.002 0.455 0.010 -0.131 0.361 -0.517 0.050 0.519 0.277 Age 0.107 0.192 0.034 0.682 0.063 0.048 -0.008 0.771 -0.048 0.334 0.065 0.449 Straight* -0.581 0.556 -0.622 0.530 -0.178 0.638 0.520 0.096 0.523 0.359 0.885 0.393 Black* 0.635 0.415 0.504 0.519 -0.408 0.173 0.323 0.190 0.247 0.584 -0.629 0.442 Other Race* 0.174 0.844 -0.130 0.883 0.292 0.388 -0.287 0.303 0.061 0.905 0.473 0.609 Education 0.360 0.469 0.609 0.222 -0.023 0.904 -0.113 0.471 0.326 0.260 0.015 0.977 Years In School 0.389 0.039 0.471 0.013 -0.113 0.115 -0.035 0.557 -0.100 0.365 -0.302 0.125 Traditional Student* 0.390 0.683 0.032 0.973 0.440 0.230 0.019 0.950 0.021 0.971 0.639 0.523 Parent #1‟s Education 0.089 0.625 0.105 0.562 -0.031 0.659 -0.017 0.769 0.057 0.583 -0.047 0.806 Parent #1‟s Occupational Prestige 0.041 0.029 0.035 0.067 0.001 0.896 0.005 0.411 -0.001 0.954 0.017 0.402 R2 0.160 0.159 0.088 0.064 0.066 0.043 Adjusted R2 0.109 0.108 0.032 0.007 0.009 -0.015 F-Test 3.132 0.001 3.109 0.001 1.58 0.117 1.115 0.354 1.161 0.321 0.743 0.683 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status ** N = 174

Table 7: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Female Genital Term Variables Are Regressed on Demographic Variables (N = 175)1 # of Words # of Slang Avg. Use Avg. Off. Off Var.** Avg. Use*Off. Independent Variables b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. Constant 1.256 0.666 -0.701 0.783 0.567 0.660 4.600 0.002 2.725 0.298 1.748 0.689 Sex (1 = male) 0.290 0.516 0.349 0.373 0.179 0.366 0.072 0.750 -1.021 0.012 1.132 0.092 Age 0.036 0.654 0.035 0.616 -0.002 0.961 -0.028 0.491 -0.078 0.284 -0.051 0.673 Straight* -0.009 0.993 0.092 0.914 -0.554 0.198 0.256 0.604 1.007 0.267 0.390 0.788 Black* 0.254 0.739 0.517 0.441 -0.158 0.640 -0.036 0.926 0.197 0.782 -1.003 0.382 Other Race* -0.291 0.736 -0.257 0.735 0.260 0.497 0.191 0.665 0.027 0.973 0.850 0.513 Education 0.657 0.179 0.843 0.050 0.441 0.042 -0.425 0.088 -0.127 0.771 0.719 0.327 Years In School 0.357 0.053 0.273 0.092 0.009 0.909 -0.038 0.685 0.050 0.764 0.039 0.887 Traditional Student* -0.446 0.634 0.207 0.801 0.299 0.470 -0.374 0.432 0.503 0.550 -1.268 0.367 Parent #1‟s Education 0.156 0.379 0.116 0.458 0.018 0.817 0.065 0.469 0.240 0.140 0.171 0.521 Parent #1‟s Occupational Prestige 0.013 0.486 0.022 0.166 0.002 0.760 -0.004 0.652 -0.006 0.708 0.016 0.569 R2 0.080 0.091 0.047 0.037 0.093 0.050 Adjusted R2 0.024 0.035 -0.011 -0.022 0.036 -0.008 F-Test 1.425 0.173 1.640 0.100 0.804 0.625 0.622 0.793 1.625 0.104 0.862 0.570 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status ** N = 170

Male Genital Slang Term Categories

Overall, only 25 of the 240 coefficients for the six categories for male genital slang terms obtained significance, which is approximately what would be expected by chance (see Table 8 and Appendices E, F, and G). However, of the six categories for male genital slang terms, only the Authority category contained more significant findings than would be expected by chance.

As seen in Table 8, when the category variables related to the male genital terms were regressed on the demographic variables, 9 of the 20 coefficients obtain statistical significance at the p < 0.1 level.

For every one year increase in age, respondents, on average, list 0.014 fewer male genital slang terms that were categorized as authority, have 0.8% fewer authority slang terms listed (see

Table 8). Furthermore, for every one year increase in age, respondents have 0.02 units less average offensiveness for authority slang terms. For every one year increase in working toward their current degree, respondents, on average, have 1.4% more authority slang terms in their list of male slang terms. Traditional students, on average, list 0.15 fewer authority slang terms, have

12% fewer authority slang terms, and have 0.23 units less on average offensive for authority slang terms. For every one level increase in parent #1‟s education attainment, on average respondents list 0.04 more authority slang terms. To summarize, the older a respondent was, the fewer authority terms they listed. In general, the higher a respondent‟s parent‟s education level and occupational prestige was, the more they listed and took offense to authority slang terms for the male genitals.

Table 8: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Authority Categories for Male Genital Slang Terms Are Regressed on Demographic Variables (N = 175)1 Authority (♂) Number Percent Avg. Use Avg. Off. Independent Variables b Sig. b Sig. b Sig. b Sig. Constant 0.278 0.293 0.298 0.000 0.027 0.957 0.392 0.286 Sex (1 = male) -0.012 0.768 -0.013 0.305 0.097 0.204 -0.033 0.553 Age -0.014 0.062 -0.008 0.000 -0.012 0.372 -0.022 0.034 Straight* -0.049 0.579 0.014 0.613 0.117 0.479 -0.022 0.858 Black* 0.002 0.973 -0.011 0.600 -0.061 0.639 0.040 0.682 Other Race* -0.072 0.361 -0.019 0.423 -0.102 0.492 -0.090 0.411 Education 0.044 0.317 -0.011 0.431 0.063 0.450 0.078 0.209 Years In School 0.018 0.280 0.014 0.008 0.035 0.260 0.027 0.252 Traditional Student* -0.153 0.074 -0.120 0.000 -0.040 0.801 -0.233 0.050 Parent #1‟s 0.038 0.018 0.004 0.428 0.026 0.391 0.050 0.026 Education Parent #1‟s Occupational -0.003 0.136 -0.001 0.137 -0.004 0.157 -0.004 0.107 Prestige R2 0.071 0.143 0.044 0.079 Adjusted R2 0.015 0.091 -0.014 0.023 F-Test 1.259 0.258 2.735 0.004 0.757 0.670 1.402 0.183 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Female Genital Slang Term Categories

Overall, 36 of the 230 coefficients tested when category variables for female genital terms were regressed on demographic variables obtained significance at p < 0.1 (see Tables 9 and 10 and Appendix H). Of these 36 significant coefficients, 17 were differences regarding gender (see Tables 9 and 10 and Appendix H). Men, on average, list 0.11 more abject slang terms, have 2.2% more abject slang terms among their listed slang terms for the female genitals, and have 0.37 units more for average use of abject slang terms (see Table 9). Being a male respondent increased the odds of listing the word “cunt” as a female genital slang term by 2.62

(see Table 11). Men, on average, had 0.85 more points than women for the use of the word cunt when it was listed (see Table 11). Women, on average, list 0.25 more euphemistic slang terms and 0.55 more nonsense slang terms for the female genitals and have 4.3% more euphemistic slang terms and 11.8% more nonsense slang terms in their listed slang terms (see Tables 9 and

10).

43 Table 9: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Abject and Euphemism Categories for Female Genital Slang Terms Are Regressed on Demographic Variables (N = 175)1 Abject (♀) Euphemism (♀)

Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off. Independent Variables b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. Constant -0.192 0.590 -0.045 0.422 -0.212 0.796 0.491 0.690 0.054 0.916 0.029 0.754 0.997 0.453 -0.075 0.903 Sex (1 = male) 0.109 0.046 0.022 0.013 0.365 0.004 0.214 0.257 -0.247 0.002 -0.043 0.003 -0.490 0.017 -0.291 0.002 Age 0.020 0.039 0.004 0.016 0.012 0.583 0.019 0.572 0.014 0.332 0.002 0.478 -0.013 0.728 0.018 0.294 Straight* -0.050 0.670 -0.006 0.759 -0.420 0.125 -0.248 0.545 -0.211 0.216 -0.030 0.329 -0.505 0.254 -0.118 0.567 Black* -0.071 0.446 -0.005 0.710 0.415 0.056 -0.288 0.375 0.077 0.564 0.010 0.674 0.129 0.713 0.043 0.793 Other Race* -0.079 0.454 -0.012 0.489 0.098 0.689 -0.432 0.239 -0.229 0.132 -0.037 0.170 -0.485 0.220 -0.231 0.210 Education -0.105 0.080 -0.016 0.097 -0.042 0.757 -0.236 0.255 0.120 0.161 0.013 0.396 0.141 0.526 0.061 0.558 Years In School 0.019 0.395 0.001 0.864 -0.021 0.682 0.094 0.225 -0.027 0.397 -0.006 0.317 -0.035 0.674 -0.038 0.332 Traditional -0.010 0.931 0.008 0.655 0.255 0.333 -0.262 0.509 -0.109 0.506 -0.001 0.979 0.123 0.773 0.022 0.912 Student* Parent #1‟s 0.029 0.182 0.004 0.209 0.046 0.359 0.008 0.915 -0.045 0.153 -0.011 0.048 -0.170 0.037 -0.046 0.223 Education Parent #1‟s Occupational 0.001 0.636 0.000 0.905 0.001 0.860 0.008 0.323 0.004 0.207 0.001 0.090 0.017 0.051 0.006 0.125 Prestige R2 0.128 0.127 0.097 0.059 0.138 0.12 0.098 0.101 Adjusted R2 0.075 0.073 0.042 0.001 0.085 0.066 0.043 0.046 F-Test 2.407 0.011 2.377 0.012 1.759 0.072 1.023 0.427 2.626 0.005 2.234 0.018 1.774 0.069 1.846 0.056 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Table 10: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Nonsense and Euphemism+Nonsense Categories for Female Genital Slang Terms Are Regressed on Demographic Variables (N = 175)1 Nonsense (♀) Euphemism and Nonsense (♀) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off. Independent Variables b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. Constant 0.691 0.491 0.362 0.046 1.749 0.365 1.281 0.300 0.744 0.508 0.391 0.039 2.746 0.259 1.205 0.383 Sex (1 = male) -0.548 0.000 -0.118 0.000 -0.747 0.012 -0.418 0.028 -0.795 0.000 -0.160 0.000 -1.237 0.001 -0.709 0.001 Age -0.007 0.795 -0.003 0.547 -0.036 0.499 -0.018 0.590 0.006 0.835 -0.001 0.815 -0.049 0.467 0.000 0.991 Straight* 0.379 0.257 0.094 0.119 -0.583 0.364 0.494 0.230 0.168 0.653 0.065 0.303 -1.089 0.180 0.377 0.413 Black* 0.332 0.209 0.024 0.612 -0.220 0.664 0.674 0.039 0.409 0.167 0.034 0.489 -0.091 0.886 0.717 0.049 Other Race* 0.253 0.397 0.036 0.509 0.536 0.351 -0.039 0.916 0.023 0.944 -0.002 0.972 0.051 0.943 -0.270 0.511 Education -0.086 0.608 -0.040 0.189 0.297 0.360 -0.130 0.530 0.034 0.857 -0.027 0.394 0.438 0.283 -0.069 0.765 Years In School 0.052 0.409 0.005 0.661 0.232 0.058 0.050 0.521 0.025 0.726 -0.001 0.947 0.197 0.199 0.012 0.890 Traditional 0.025 0.939 -0.013 0.830 -0.037 0.952 0.032 0.936 -0.085 0.815 -0.013 0.826 0.086 0.913 0.054 0.903 Student* Parent #1‟s 0.055 0.372 0.001 0.910 -0.162 0.170 0.087 0.248 0.010 0.884 -0.010 0.390 -0.332 0.026 0.041 0.626 Education Parent #1‟s Occupational -0.001 0.815 -0.002 0.163 0.011 0.390 -0.011 0.155 0.003 0.715 -0.001 0.606 0.027 0.080 -0.005 0.558 Prestige R2 0.102 0.142 0.098 0.079 0.140 0.195 0.132 0.104 Adjusted R2 0.48 0.089 0.043 0.023 0.088 0.145 0.079 0.049 F-Test 1.873 0.052 2.710 0.004 1.775 0.069 1.404 0.183 2.679 0.005 3.961 0.000 2.484 0.008 1.901 0.048 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Table 11: R2, Adjusted R2, F-Test Values, Χ², Nagelkerke R2, Unstandardized Coefficients, Log Odds, and Significance Values when Dummy Variable for the Listing of “Cunt”, Use of “Cunt”, and Perceived Offensiveness to “Cunt” Are Regressed on Demographic Variables (N = 175)1 “Cunt” Listed* Use Offensiveness Independent Variables Exp(B) Sig. b Sig. b Sig. Constant 1.379 0.898 -1.340 0.359 3.114 0.319 Sex (1 = male) 2.618 0.009 0.852 0.000 0.541 0.259 Age 1.009 0.898 0.012 0.776 -0.038 0.664 Straight* 0.241 0.122 -0.563 0.248 -0.786 0.450 Black* 0.196 0.015 -0.544 0.157 -0.916 0.265 Other Race* 0.409 0.199 0.151 0.728 -1.039 0.265 Education 0.857 0.694 0.307 0.210 -0.378 0.471 Years In School 1.197 0.235 0.044 0.634 0.188 0.340 Traditional Student* 0.675 0.633 0.444 0.345 -0.235 0.815 Parent #1‟s Education 1.354 0.026 0.082 0.361 0.395 0.040 Parent #1‟s Occupational 0.999 0.904 0.006 0.495 0.007 0.723 Prestige R2 0.22 (Nagelkerke) 0.140 0.083 Adjusted R2 - 0.087 0.027 F-Test Χ² = 2.664 0.001 2.664 0.005 1.491 0.147 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Additionally, women, on average, have 0.49 more units for average use of euphemistic slang terms and have 0.75 more units for average use of nonsense slang terms (see Tables 9 and 10).

Women also have 0.29 more units for average offensiveness of euphemistic slang terms and 0.42 more units for average offensiveness of nonsense slang terms on average (see Tables 9 and 10).

The trend of more terms, more use, and more offensiveness for women holds true for the euphemism+nonsense variables as well (see Table 10). In sum, men know and use more abject slang terms for the female genitals and women list, use, and find more offensive euphemistic and nonsense terms for the female genitals.

In sum, demographic variables had significant impact on the slang-related variables. As found by other authors, the gender of the respondent has a significant effect on the most variables though other demographic variables had a number of significant regression coefficients.

Hypothesis 2: Demographic characteristics have significant effects on sexism.

Tables 12, 13, and 14 show the results when the sexism scales (mentioned above) were regressed on the demographic variables age, highest educational degree attained, years in school, parent #1‟s educational attainment, and parent #1‟s occupational prestige score as well as the dichotomous variables sex/gender, straight, black, other race, and traditional student. A total of

35 of 120 coefficients were significant at the p < 0.1 level.

As seen in Tables 12, 13, and 14, men were more likely to have significantly higher scores on all but 2 of the 12 subscales created from the sexism scales. From the Ambivalent

Sexism Inventory, on average men have 0.77 more points on the Hostile subscale, 0.63 more points on the Anti-Feminism subscale, 0.7 more points on the Protective Paternalism subscale, and 0.5 fewer points on the Complementary Gender Differentiation subscale (see Table 12).

Men have significantly higher scores on the Modern Sexism Scale subscales, with 0.69 more points on the Against Special Treatment subscale and 0.41 more points on the Equality Attained subscale on average (see Table 13). On the Sexual Beliefs Scale, on average men have 0.78 more points on the Token Resistance subscale, 0.45 more points on the Leading On Justifies

Force subscale, 0.66 more points on the Women Like Force subscale, and 0.87 more points on the Men Should Dominate subscale. In sum, men score significantly higher on most sexism subscales (see Table 14). This is not surprising given the persistence of patriarchy in American society, despite a change in types of sexism (see Spence and Kahn 1997).

47 Table 12: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Ambivalent Sexism Inventory Subscales are Regressed on Demographic Variables (N = 175)1 Complementary Heterosexual Protective Hostile Anti-Feminism Gender Intimacy Paternalism Differentiation Independent Variables b Sig. b Sig. b Sig. b Sig. b Sig. Constant 4.236 0.000 5.272 0.000 4.828 0.001 6.974 0.000 5.122 0.000 Sex (1 = male) 0.796 0.000 0.629 0.004 0.102 0.635 0.696 0.000 -0.495 0.011 Age -0.040 0.224 0.008 0.844 -0.019 0.622 -0.070 0.031 -0.042 0.231 Straight* 0.932 0.018 1.003 0.032 0.822 0.080 0.699 0.074 0.845 0.044 Black* 0.320 0.301 -0.349 0.342 0.848 0.023 0.475 0.124 0.543 0.100 Other Race* 0.176 0.615 0.074 0.858 0.174 0.677 -0.067 0.847 -0.164 0.659 Education -0.186 0.345 -0.446 0.058 -0.153 0.516 -0.212 0.280 -0.105 0.616 Years In School 0.039 0.598 -0.004 0.965 -0.041 0.641 0.022 0.764 0.047 0.556 Traditional Student* 0.230 0.543 -0.033 0.942 0.109 0.809 -0.390 0.301 -0.020 0.960 Parent #1‟s Education -0.068 0.345 -0.040 0.642 -0.044 0.607 -0.091 0.206 -0.139 0.070 Parent #1‟s -0.004 0.568 -0.021 0.018 -0.019 0.030 -0.012 0.119 -0.010 0.210 Occupational Prestige R2 0.147 0.128 0.092 0.159 0.149 Adjusted R2 0.095 0.075 0.037 0.108 0.097 F-Test 2.820 0.003 2.409 0.011 1.664 0.093 3.109 0.001 2.867 0.003 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Table 13: Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Modern Sexism Scale Subscales are Regressed on Demographic Variables (N = 175)1 Against „Special Treatment‟ Equality Attained Independent Variables b Sig. b Sig. Constant 4.257 0.000 4.332 0.000 Sex (1 = male) 0.692 0.000 0.405 0.006 Age -0.005 0.858 0.015 0.574 Straight* 0.406 0.259 0.442 0.167 Black* -0.336 0.236 -0.024 0.923 Other Race* -0.467 0.147 0.033 0.907 Education -0.123 0.498 -0.380 0.019 Years In School -0.101 0.140 -0.134 0.028 Traditional Student* 0.178 0.608 0.453 0.143 Parent #1‟s Education -0.114 0.084 -0.153 0.009 Parent #1‟s -0.008 0.255 -0.002 0.765 Occupational Prestige R2 0.168 0.162 Adjusted R2 0.117 0.111 F-Test 3.312 0.001 3.178 0.001 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Table 14: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Sexual Beliefs Scale Subscales are Regressed on Demographic Variables (N = 175)1 Leading On Men Should Token Resistance Women Like Force No Means Stop Justifies Force Dominate Independent Variables b Sig. b Sig. b Sig. b Sig. b Sig. Constant 3.265 0.007 2.824 0.005 4.781 0.000 2.322 0.055 6.992 0.000 Sex (1 = male) 0.777 0.000 0.448 0.003 0.660 0.001 0.872 0.000 -0.108 0.132 Age -0.041 0.221 -0.024 0.384 -0.024 0.496 0.034 0.307 -0.004 0.762 Straight* 0.972 0.016 0.360 0.273 0.746 0.078 0.955 0.018 0.028 0.857 Black* 0.241 0.445 -0.481 0.065 0.495 0.138 0.531 0.095 0.010 0.936 Other Race* -0.057 0.872 0.436 0.138 0.129 0.732 0.774 0.032 0.020 0.885 Education -0.143 0.477 -0.237 0.153 -0.220 0.302 -0.078 0.700 -0.018 0.815 Years In School 0.026 0.730 0.010 0.878 -0.035 0.661 -0.087 0.253 -0.020 0.504 Traditional Student* 0.555 0.151 0.027 0.933 0.580 0.156 0.220 0.570 -0.065 0.664 Parent #1‟s Education -0.186 0.012 -0.144 0.018 -0.150 0.054 -0.071 0.334 0.035 0.214 Parent #1‟s 0.004 0.632 0.007 0.271 -0.006 0.491 -0.012 0.131 -0.003 0.360 Occupational Prestige R2 0.173 0.134 0.139 0.189 0.030 Adjusted R2 0.122 0.081 0.086 0.140 -0.029 F-Test 3.427 0.000 2.533 0.007 2.637 0.005 3.829 0.000 0.510 0.881 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

50 For every one year increase in age, on average respondents had 0.07 fewer points on the

Protective Paternalism subscale (see Table 12). Black respondents had an average of 0.85 more points on the Heterosexual Intimacy subscale and 0.54 more points on the Complementary

Gender Differentiation subscale of the Ambivalent Sexism Inventory (see Table 12). They also had an average of 0.48 fewer points on the Leading On Justifies Force subscale and 0.53 more points on the Men Should Dominate subscale of the Sexual Beliefs Scale (see Table 14).

Respondents who did not self-identify as white or black had an average of 0.77 more points on the Men Should Dominate subscale of the Sexual Beliefs Scale (see Table 14).

Respondents who identified as straight were significantly more likely to have higher scores on a number of sexism subscales. From the Ambivalent Sexism Inventory, on average straight respondents had 0.93 more points on the Hostile subscale, 1.00 more points on the Anti-

Feminism subscale, 0.82 more points on the Heterosexual Intimacy subscale, 0.7 more points on the Protective Paternalism subscale, and 0.85 more points on the Complementary Gender

Differentiation subscale (see Table 12). On the Sexual Beliefs Scale, straight respondents, on average, had 0.97 more points on the Token Resistance subscale, 0.75 more points on the

Women Like Force subscale, and 0.96 more points on the Men Should Dominate subscale (see

Table 14). In sum, straight respondents had significantly higher scores on the Ambivalent

Sexism Inventory and Sexual Beliefs Scale indicating higher levels of sexism and greater acceptance of myths about rape.

For every one level increase in educational attainment by the respondent, on average there were 0.45 fewer points on the Anti-Feminism subscale of the Ambivalent Sexism Inventory and 0.38 fewer points on the Equality Attained subscale of the Modern Sexism Scale (see Table

12). Similarly, for every additional year spent working toward their current degree, respondents on average had 0.13 fewer points on the Equality Attained subscale (see Table 13).

For every one level increase in educational attainment by parent #1, respondents on average had 0.14 fewer points on the Complementary Gender Differentiation subscale of the

Ambivalent Sexism Inventory (see Table 12), 0.11 fewer points on the Against Special

Treatment subscale and 0.15 fewer points on the Equality Attained subscale of the Modern

Sexism Scale (see Table 13), 0.19 fewer points on the Token Resistance subscale, 0.14 fewer points on the Leading On Justifies Force subscale, and 0.15 fewer points on the Women Like

Force subscale of the Sexual Beliefs Scale (see Table 14).

In sum, all demographic variables except being a traditional student had significant effects on at least one of the subscales from the three sexism scales. Gender, sexual orientation, and parental SES had the most significant effects. Overall, men and straight people have higher scores on the sexism scales. However, higher education and occupational prestige scores by the respondent‟s parent #1 (usually mother) resulted in lower sexism scores.

Hypothesis 3: Slang knowledge, use, offensiveness, and categories are significantly correlated with sexism.

Tables 15 and 16 show the correlation coefficients and significance levels when the slang-related variables (excluding the category variables) were correlated with the 12 sexism scale subscales. These are strictly correlation coefficients with no control variables. A total of

30 of 144 correlations were significant at the p < 0.1 level. Though no causation is implied by these hypotheses, for ease of understanding I will frame the results as “differences in slang correlating with sexism scores.”

52 Table 15: Correlations and Significance Values Between Male Genital Term Variables and Sexism Scale Subscales (N = 175)1 # of Words # of Slang Avg. Use Avg. Off. Off. Variance* Avg. Use*Off. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. Ambivalent Sexism Inventory Hostile 0.096 0.205 0.089 0.240 0.208 0.006 0.096 0.207 0.055 0.471 0.187 0.013 Anti-Feminism -0.004 0.959 -0.009 0.909 0.098 0.198 0.100 0.190 0.008 0.920 0.182 0.016 Heterosexual Intimacy 0.021 0.778 0.014 0.853 0.072 0.341 0.075 0.325 -0.024 0.749 0.073 0.336 Protective Paternalism -0.018 0.811 -0.017 0.825 0.130 0.085 -0.037 0.629 -0.076 0.319 0.005 0.947 Comp. Gender Differentiation -0.144 0.057 -0.166 0.028 0.027 0.722 0.156 0.040 0.109 0.152 0.094 0.217 Modern Sexism Scale

Against „Special Treatment‟ 0.067 0.379 0.087 0.253 0.054 0.481 0.110 0.146 -0.035 0.644 0.131 0.084 Equality Attained 0.300 0.696 0.002 0.981 0.074 0.327 0.023 0.762 -0.083 0.277 0.018 0.811 Sexual Beliefs Scale

Token Resistance -0.018 0.813 -0.042 0.585 0.176 0.019 0.052 0.496 0.012 0.872 0.123 0.106 Leading On Justifies Force 0.108 0.155 0.102 0.178 0.072 0.342 0.165 0.029 0.088 0.247 0.168 0.026 Women Like Force 0.042 0.579 0.036 0.632 0.141 0.063 0.034 0.656 0.022 0.776 0.096 0.205 Men Should Dominate 0.034 0.655 0.029 0.705 0.213 0.005 0.060 0.432 0.021 0.781 0.173 0.022 No Means Stop -0.118 0.119 -0.114 0.132 -0.055 0.468 -0.051 0.504 -0.002 0.984 -0.021 0.778 1 Bold indicates significance at p < 0.1 * N = 174

Table 16: Correlations and Significance Values Between Female Genital Term Variables and Sexism Scale Subscales (N = 175)1 # of Words # of Slang Avg. Use Avg. Off. Off. Variance* Avg. Use*Off. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. Ambivalent Sexism Inventory Hostile 0.086 0.260 0.045 0.551 0.212 0.005 -0.061 0.421 -0.053 0.495 0.137 0.071 Anti-Feminism -0.066 0.387 -0.112 0.139 0.140 0.064 -0.014 0.850 -0.015 0.845 0.137 0.071 Heterosexual Intimacy 0.112 0.138 0.074 0.331 0.184 0.015 -0.044 0.565 -0.018 0.813 0.096 0.207 Protective Paternalism -0.023 0.758 -0.037 0.631 0.160 0.034 -0.131 0.085 -0.149 0.053 -0.035 0.649 Comp. Gender Differentiation -0.014 0.854 -0.050 0.515 0.086 0.258 -0.016 0.838 0.073 0.343 -0.005 0.946 Modern Sexism Scale

Against „Special Treatment‟ -0.056 0.458 -0.077 0.310 0.085 0.261 -0.034 0.657 -0.125 0.104 0.070 0.358 Equality Attained -0.080 0.290 -0.129 0.088 0.140 0.064 -0.127 0.094 -0.139 0.070 0.033 0.663 Sexual Beliefs Scale

Token Resistance -0.540 0.476 -0.076 0.315 0.176 0.020 -0.056 0.460 -0.091 0.236 0.126 0.097 Leading On Justifies Force 0.008 0.917 0.048 0.532 0.054 0.482 -0.017 0.822 -0.149 0.052 0.066 0.386 Women Like Force -0.039 0.606 -0.041 0.590 0.142 0.061 -0.019 0.804 -0.063 0.411 0.084 0.269 Men Should Dominate -0.012 0.871 -0.031 0.684 0.053 0.482 -0.011 0.880 -0.028 0.716 0.114 0.132 No Means Stop -0.015 0.843 -0.054 0.480 -0.049 0.518 0.019 0.804 0.090 0.241 -0.011 0.883 1 Bold indicates significance at p < 0.1 * N = 170

54 In general, there is a weak5 tendency for respondents who listed more terms and more slang terms for the male genitals to score lower on the Complementary Gender Differentiation scale (see Table 15). Average use had significant positive correlations with five sexism scale subscales. There was a weak tendency for respondents who indicated higher levels of average use of male genital terms to have higher scores on the Hostile and Protective Paternalism scales from the Ambivalent Sexism Inventory and higher scores on the Token Resistance, Women Like

Force, and Men Should Dominate scales of the Sexual Beliefs Scale (see Table 15). In other words, the higher the average use of male genital terms, the larger were the scores on sexism subscales, especially male-dominance related subscales.

There was a weak correlation between respondents who indicated higher levels of average offensiveness to male genital terms and higher scores on both the Complementary

Gender Differentiation scale and the Leading On Justifies Force scale (see Table 15). The variance of the offensiveness of male genital terms was not significantly correlated with any sexism subscale.

Last, the use-offensiveness interaction term was significantly and positively correlated with four sexism subscales, though they were not the same as the ones correlated with average use. Again, higher scores on the use-offensiveness interaction term reflect simultaneous high use and high perceived offensiveness for genital terms. Participants who had higher scores on the use-offensiveness interaction term tended to have higher scores on the Hostile scale, the Anti-

Feminism scale, the Against „Special Treatment‟ scale, the Leading On Justifies Force scale, and the Men Should Dominate scale (see Table 15).

No significant correlations were found for the number of female genital terms listed (see

Table 16). However, respondents who listed more slang terms for the female genitals had a weak tendency to score lower on the Equality Attained scale of the Modern Sexism Scale. Thus, similar to male genital terms and slang, the ability to list genital terms does not significantly correlate with many sexism subscales.

Average use of female genital terms, however, does significantly and positively correlate with 7 of the 12 sexism subscales (see Table 16). Respondents who had higher levels of average use of female genital terms tended to have higher scores on the Hostile scale, the Anti-Feminism scale, the Heterosexual Intimacy scale, and the Protective Paternalism scale from the Ambivalent

Sexism Inventory (see Table 16). Additionally, respondents with higher levels of average use of female genital terms tended to have higher scores on the Equality Attained scale of the Modern

Sexism Scale and higher scores on the Token Resistance scale and the Women Like Force scale of the Sexual Beliefs Scale (see Table 16). In sum, the more female genital terms were used on average, the higher the scores were on more than half of the sexism subscales.

Average offensiveness and the variance of offensiveness for female genital terms were significantly negatively correlated with three sexism subscales (see Table 16). There was a weak tendency for respondents who had higher levels of average perceived offensiveness to female genital terms to have lower scores on the Protective Paternalism scale and the Equality

Attained scale. Similarly, respondents who had higher levels of variance of offensiveness to female genital terms weakly tended to have lower scores on the Protective Paternalism scale, the

Equality Attained scale, and the Leading On Justifies Force scale (see Table 16). In sum, the more a participant found female genital terms offensive on average, the less sexist they were on certain subscales. Additionally, the more varied their offensiveness scores, the less sexist they

were on certain subscales. This may be indicative of a connection between conscientious thought regarding the terms‟ offensiveness and conscientious thought regarding gender issues.

Last, the use-offensiveness interaction term for female genital terms was significantly positively correlated with three sexism subscales (see Table 16). There was a weak tendency for respondents who had higher values for the use-offensiveness interaction term for female genital terms to have higher scores on the Hostile scale, the Anti-Feminism scale, and the Token

Resistance scale. In other words, the more a respondent used a word while also finding it offensive, the higher scores they had on these three sexism subscales.

Male Genital Slang Term Categories

As seen in Tables 17 and Appendices I, J, and K, there were a total of 16 of 288 significant correlations at the p < 0.1 level between the slang category variables for male genital slang and the sexism subscales. Interestingly, half of the 16 significant correlations were among the danger category variables.

Respondents who listed more slang terms for the male genitals that frame the genitals as dangerous or violent tended to have lower scores on the Complementary Gender Differentiation and Token Resistance scales (see Table 17). Similarly, there was a weak tendency for respondents who had more danger terms comprise the total list of slang terms to have lower scores on the Token Resistance scale. In other words, listing more danger terms for the male genitals significantly correlated with lower scores on the Complementary Gender Differentiation scale and the Token Resistance scale indicating less agreement with complementary gender differentiations (e.g., women have refined tastes) and the stereotype that women give token

resistance in sexual situations. This finding is unexpected and will be explored further in the discussion section.

Table 17: Correlations and Significance Values Between Danger Category Variables for Male Genital Slang Terms and Sexism Scale Subscales (N = 175)1 Danger (♂) Number Percent Avg. Use Avg. Off. r Sig. r Sig. r Sig. r Sig. Ambivalent Sexism Inventory Hostile -0.042 0.580 -0.049 0.523 0.053 0.488 -0.053 0.486 Anti-Feminism -0.108 0.156 -0.102 0.181 0.022 0.771 -0.159 0.036 Heterosexual Intimacy 0.008 0.914 0.005 0.952 0.047 0.536 -0.060 0.428 Protective Paternalism -0.065 0.395 -0.054 0.477 0.045 0.554 -0.112 0.138 Comp. Gender Differentiation -0.129 0.088 -0.115 0.128 0.013 0.866 -0.160 0.035 Modern Sexism Scale

Against „Special Treatment‟ 0.049 0.520 0.052 0.496 0.075 0.326 0.008 0.921 Equality Attained -0.020 0.789 -0.033 0.662 0.079 0.297 -0.077 0.309 Sexual Beliefs Scale

Token Resistance -0.126 0.095 -0.132 0.081 0.040 0.602 -0.112 0.142 Leading On Justifies Force 0.028 0.709 -0.020 0.790 0.180 0.017 0.002 0.982 Women Like Force -0.085 0.261 -0.083 0.277 0.038 0.620 -0.092 0.228 Men Should Dominate -0.121 0.110 -0.108 0.156 0.035 0.646 -0.176 0.020 No Means Stop -0.065 0.396 0.016 0.833 -0.235 0.002 0.014 0.858 1 Bold indicates significance at p < 0.1

There was a weak tendency for respondents who had high levels of average use of danger terms for the male genitals to score higher on the Leading On Justifies Force scale and score lower on the No Means Stop scale (see Table 17). Recall that higher scores on the No Means

Stop subscale of the Sexual Beliefs Scale means greater levels of agreement that saying no during a sexual encounter does indeed mean stop. Thus, using danger slang terms for the male genitals correlated with higher agreement that „if a woman sexually leads on a man, then the man is justified in using force on her‟ and lower agreement that „saying no during a sexual encounter means stop.”

Completing the danger slang category, average offensiveness of slang in this category was significantly negatively correlated with three sexism subscales. Respondents who have higher levels of average offensiveness tended to score lower on the Anti-Feminism,

Complementary Gender Differentiation, and Men Should Dominate scales (see Table 17). In

sum, higher values of average perceived offensiveness for danger slang for the male genitals was significantly correlated with lower scores on three sexism subscales.

In sum, only the danger category for male genital slang terms contained more than expected significant findings. Knowledge and perceived offensiveness of these terms correlated with lower levels of sexism. However, use correlated with higher levels of sexism, specifically that “no” does not mean “stop” in a sexual situation and that if a woman leads on a man sexually, she deserves what is “coming to her.” However, overall there were fewer significant findings than would be expected by chance for all of the male genital slang term category variables.

Female Genital Slang Term Categories

Among the female genital slang term categories, a total of 31 of 324 correlations were significant at the p < 0.1 level (see Tables 18 and 19 and Appendices L, M, and N). Nearly one third of the 31 significant correlations were within the “cunt” category.

The euphemism category for female slang terms contained 8 significant correlations, 7 of which were negative (Table 18). There was a weak tendency for respondents who listed more euphemistic slang terms for the female genitals to score lower on the Complementary Gender

Differentiation scale and the Token Resistance scale. Respondents who had euphemistic slang terms for the female genitals comprise higher percents of all listed slang terms for the female genitals tended to score lower on the Token Resistance scale. There was a weak tendency for respondents who had higher levels of average use of euphemistic slang terms for the female genitals to score higher on the Leading On Justifies Force and lower on the No Means Stop scales. Finally, there was a weak tendency for respondents who had higher levels of average offensiveness to euphemistic slang terms for the female genitals to score lower on the Anti-

Feminism, Complementary Gender Differentiation, and Men Should Dominate scales. To summarize, listing and perceived offensiveness of euphemistic slang for the female genitals was correlated with lower levels of sexism. However, using euphemistic slang for the female genitals was correlated with higher levels of sexism. Some of these correlations may be spurious due to the fact the women tended to list, use, and take offense to euphemistic slang terms more than men and had lower levels of sexism compared to men.

Table 18: Correlations and Significance Values Between Euphemism Category Variables for Female Genital Slang Terms and Sexism Scale Subscales (N = 175)1 Euphemism (♀)

Number Percent Avg. Use Avg. Off.

r Sig. r Sig. r Sig. r Sig.

Ambivalent Sexism Inventory

Hostile -0.042 0.580 -0.049 0.523 0.053 0.488 -0.053 0.486 Anti-Feminism -0.108 0.156 -0.102 0.181 0.022 0.771 -0.159 0.036 Heterosexual Intimacy 0.008 0.914 0.005 0.952 0.047 0.536 -0.060 0.428 Protective Paternalism -0.065 0.395 -0.054 0.477 0.045 0.554 -0.112 0.138 Comp. Gender Differentiation -0.129 0.088 -0.115 0.128 0.013 0.866 -0.160 0.035 Modern Sexism Scale

Against „Special Treatment‟ 0.049 0.520 0.052 0.496 0.075 0.326 0.008 0.921 Equality Attained -0.020 0.789 -0.033 0.662 0.079 0.297 -0.077 0.309 Sexual Beliefs Scale

The final category of “cunt” contained 10 significant correlations (Table 19). There was a weak tendency for respondents who listed this term to score lower on the Complementary

Gender Differentiation and Equality Attained scales. There was also a weak tendency for respondents who used the term “cunt” more often to score higher on the Hostile scale and lower on the Complementary Gender Differentiation scale. Use was also correlated with 4 of the 5 subscales of the Sexual Beliefs Scale. There was a weak tendency for respondents who used

“cunt” more often to score higher on the Token Resistance, Leading On Justifies Force, and Men

Should Dominate scales and lower on the No Means Stop scale. Last, there was a weak tendency for respondents with higher levels of perceived offensiveness to the term “cunt” to

score lower on the Complementary Gender Differentiation and Equality Attained scales. In sum, the knowledge, use, and perceived offensiveness of the word cunt was correlated with many sexism subscales. The use of the word cunt in particular was correlated with higher levels of sexism, especially on the Sexual Beliefs Scale (a rape-myth acceptance scale).

Table 19: Correlations and Significance Values Between Listing of “Cunt”, Use of “Cunt”, and Perceived Offensiveness to “Cunt” and Sexism Scale Subscales (N = 175)1 “Cunt” Listed* Use Offensiveness r Sig. r Sig. r Sig. Ambivalent Sexism Inventory Hostile 0.037 0.622 0.159 0.036 0.016 0.838 Anti-Feminism -0.022 0.775 0.097 0.203 -0.096 0.208 Heterosexual Intimacy -0.091 0.229 0.023 0.765 -0.101 0.182 Protective Paternalism -0.050 0.508 0.036 0.632 -0.093 0.219 Comp. Gender -0.210 0.005 -0.160 0.034 -0.138 0.070 Differentiation Modern Sexism Scale

Against „Special Treatment‟ -0.081 0.289 0.072 0.344 -0.119 0.117 Equality Attained -0.163 0.031 0.054 0.477 -0.188 0.013 Sexual Beliefs Scale

Token Resistance 0.020 0.798 0.164 0.030 0.023 0.760 Leading On Justifies Force -0.013 0.864 0.214 0.005 -0.043 0.570 Women Like Force -0.059 0.440 0.108 0.154 -0.053 0.485 Men Should Dominate -0.040 0.601 0.141 0.063 -0.025 0.741 No Means Stop -0.085 0.264 -0.179 0.018 -0.036 0.633 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

To summarize, there were some significant correlations between the genital slang variables and scores on the sexism subscales. However, in hypotheses 1 and 2 we found that both the slang variables and the sexism subscales were significantly affected by demographic variables when regressed on the demographic variables. The correlations in hypothesis 3 did not control for demographic characteristics and thus there is the potential for spurious correlations.

In the following section discussing hypothesis 4, partial correlations between slang variables and sexism subscales when controlling for the demographic variables will be presented.

Hypothesis 4: Slang knowledge, use, offensiveness, and categories are significantly correlated with sexism while controlling for demographic characteristics.

Partial correlations between the various slang-related variables and the scales were computed. Unlike in Hypothesis 3 above, the demographic variables mentioned before were controlled. After controlling for demographic characteristics, 37 correlations remained significant, 38 lost significance, and 27 gained significance at the p < 0.1 level when compared to the correlations from Hypothesis 3 (see Tables 20 through 25 and Appendices O through T).

Overall, there was a net loss of 11 significant correlations by controlling for demographic characteristics. This section will discuss both new and remaining significant correlations.

Tables 20 and 21 show the partial correlations between slang variables (excluding the category variables danger, authority, abject, euphemism, nonsense, euphemism+nonsense, and

“cunt”) and the sexism subscales controlling for the demographic variables used in hypotheses 1 and 2. For the male genital term variables, 11 of 72 correlations were significant at the p < 0.1 level (Table 20).

There was a weak tendency for respondents who list more terms for the male genitals to score higher on the Leading On Justifies Force scale (Table 20). This correlation was barely significant however, with p = 0.0996. The number of slang terms listed was not significantly correlated with any of the sexism subscales.

The average use of terms for the male genitals was significantly correlated with 3 sexism subscales (Table 20). There was a weak tendency for respondents with higher of levels average use of terms for the male genitals to score higher on the Hostile, Token Resistance, and Men

Should Dominate scales. Furthermore, respondents with higher levels of average offensiveness

62 Table 20: Partial Correlations and Significance Values Between Male Genital Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 # of Words # of Slang Avg. Use Avg. Off. Off. Var. Avg. Use*Off. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. Ambivalent Sexism Inventory

Hostile 0.060 0.455 0.039 0.626 0.161 0.043 0.111 0.162 0.101 0.206 0.167 0.035 Anti-Feminism -0.027 0.739 -0.036 0.648 0.033 0.680 0.128 0.107 0.052 0.512 0.166 0.037 Heterosexual Intimacy 0.093 0.243 0.077 0.335 0.102 0.201 0.057 0.477 -0.039 0.626 0.095 0.234 Protective Paternalism -0.031 0.701 -0.049 0.537 0.103 0.197 -0.035 0.665 -0.060 0.451 -0.010 0.898 Comp. Gender Differentiation -0.067 0.401 -0.098 0.217 0.099 0.216 0.120 0.134 0.058 0.468 0.131 0.100 Modern Sexism Scale

Against „Special Treatment‟ 0.081 0.312 0.095 0.234 -0.020 0.798 0.135 0.090 0.006 0.938 0.104 0.190 Equality Attained 0.080 0.314 0.052 0.515 0.008 0.920 0.011 0.895 -0.063 0.432 -0.031 0.701 Sexual Beliefs Scale

Token Resistance -0.036 0.650 -0.076 0.342 0.180 0.023 0.036 0.654 0.037 0.641 0.109 0.173 Leading On Justifies Force 0.131 0.100 0.123 0.122 0.031 0.697 0.207 0.009 0.146 0.067 0.151 0.058 Women Like Force 0.084 0.290 0.067 0.399 0.124 0.120 0.027 0.733 0.050 0.532 0.089 0.264 Men Should Dominate -0.056 0.482 -0.057 0.473 0.159 0.045 0.093 0.244 0.084 0.294 0.161 0.043 No Means Stop -0.067 0.404 -0.064 0.422 -0.051 0.525 -0.067 0.400 -0.040 0.618 -0.026 0.742 1 Bold indicates significance at p < 0.1

63 for terms for the male genitals tended to score higher on the Against „Special Treatment‟ and

Leading On Justifies Force scales. In other words, higher levels of use and perceived offensiveness of terms for the male genitals were positively correlated with sexism.

Finally, the use-offensiveness interaction term had five significant correlations with sexism subscales (Table 20). There was a weak tendency for respondents with higher values on the use-offensiveness interaction term to scores higher on the Hostile, Anti-Feminism, and

Complementary Gender Differentiation scales. However, the correlation with the

Complementary Gender Differentiation scale was barely significant (p = 0.09992). Furthermore, there was a weak tendency for respondents with higher values on the use-offensiveness interaction term to score higher on the Leading On Justifies Force and Men Should Dominate scales. In sum, higher simultaneous rates of use and perceived offensiveness were correlated with higher levels of sexism.

To summarize, knowledge, use, and perceived offensiveness for male genital terms were all positively correlated with higher scores on sexism subscales. Moreover, the use of admittedly offensive terms is correlated with sexist attitudes. The mechanisms behind this are not immediately clear.

Table 21 shows the partial correlation controlling for the demographic variables between slang variables for the female genitals (excluding category variables danger, authority, abject, euphemism, nonsense, euphemism+nonsense, and “cunt”) and sexism subscales. A total of 11 of

72 correlations were significant at the p < 0.1 level.

Respondents who listed more terms for the female genitals tended to have higher scores on the Heterosexual Intimacy scale (Table 21). This correlation did not remain significant for

64 Table 21: Partial Correlations and Significance Values Between Female Genital Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 # of Words # of Slang Avg. Use Avg. Off. Off. Var. Avg. Use*Off. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. Ambivalent Sexism Inventory

Hostile 0.083 0.298 0.026 0.746 0.201 0.011 -0.067 0.405 -0.010 0.903 0.123 0.122 Anti-Feminism -0.079 0.320 -0.117 0.141 0.168 0.034 -0.039 0.629 0.023 0.771 0.129 0.105 Heterosexual Intimacy 0.174 0.028 0.129 0.106 0.203 0.010 -0.063 0.432 -0.017 0.836 0.125 0.116 Protective Paternalism -0.021 0.793 -0.031 0.696 0.196 0.014 -0.124 0.119 -0.119 0.136 -0.038 0.634 Comp. Gender Differentiation 0.018 0.820 -0.026 0.746 0.140 0.078 0.024 0.759 0.032 0.689 0.074 0.355 Modern Sexism Scale

Against „Special Treatment‟ -0.028 0.723 -0.052 0.514 0.071 0.373 -0.040 0.613 -0.070 0.380 0.050 0.534 Equality Attained -0.007 0.926 -0.074 0.353 0.136 0.087 -0.137 0.085 -0.111 0.165 0.049 0.544 Sexual Beliefs Scale

Token Resistance -0.028 0.726 -0.077 0.336 0.226 0.004 -0.057 0.479 -0.056 0.479 0.147 0.065 Leading On Justifies Force 0.063 0.434 0.105 0.190 0.032 0.687 -0.027 0.735 -0.117 0.143 0.042 0.598 Women Like Force 0.017 0.832 0.002 0.977 0.154 0.052 -0.028 0.726 -0.036 0.657 0.100 0.209 Men Should Dominate -0.049 0.540 -0.072 0.364 0.029 0.720 0.010 0.905 0.081 0.313 0.096 0.228 No Means Stop 0.004 0.956 -0.034 0.672 -0.028 0.728 0.000 0.996 0.042 0.598 0.005 0.946 1 Bold indicates significance at p < 0.1

65 the number of slang terms listed. Furthermore, there was a weak tendency for respondents with higher levels of average offensiveness to score lower on the Equality Attained scale. There was also a weak tendency for respondents who had higher values on the use-offensiveness interaction term to score higher on the Token Resistance scale.

Eight of the 11 of significant correlations for variables related to female genital terms

(excluding the category variables danger, authority, abject, euphemism, nonsense, euphemism+nonsense, and “cunt”) were with the average use of these terms (Table 21).

Respondents who had higher levels of average use of terms for the female genitals tended to score higher on the Hostile, Anti-Feminism, Heterosexual Intimacy, Protective Paternalism, and

Complementary Gender Differentiation scales. Furthermore, there was a weak tendency for respondents with higher levels of average use of female genital terms to score higher on the

Equality Attained, Token Resistance, and Women Like Force scales. To sum, increased levels of average use of female genital terms was positively correlated with all 5 of the Ambivalent

Sexism Inventory subscales, two of the Sexual Beliefs Scale subscales, and one of the Modern

Sexism Scale subscales.

To summarize, there were 22 of 144 significant partial correlations between the genital term variables (excluding category variables danger, authority, abject, euphemism, nonsense, euphemism+nonsense, and “cunt”) and the sexism subscales. Overall, more knowledge, use, and perceived offensiveness of genital terms listed by respondents were positively correlated with sexism. Two genital term variables contained the lion‟s share of correlations: the use- offensiveness interaction term for male genital terms and average use of female genital terms.

Over one third of the significant correlations were found in the average use of female genital terms column in Table 21.

Male Genital Slang Term Categories

Among the category variables for male genital slang terms, 13 correlations with sexism subscales were significant at the p < 0.1 level when controlling for demographic variables (see

Table 22 and Appendices O, P, and Q). Ten of these significant correlations were also significant for hypothesis 3. By controlling for demographic variables, six correlations lost significance from hypothesis 3 and three gained significance. Variables related to authority slang terms for the male genitals were not significantly correlated with any sexism subscales.

The danger category contained 7 of the 13 significant correlations in Table 22 and

Appendices O, P, and Q. There was a weak tendency for respondents who listed more danger terms for the male genitals to score lower on the Token Resistance scale (Table 22). Similarly, respondents who had danger terms comprising a larger percentage of all the terms they listed tended to have lower scores on the Token Resistance scale.

Table 22: Partial Correlations and Significance Values Between Danger Category Variables for Male Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Danger (♂) Number Percent Avg. Use Avg. Off. ρ Sig. ρ Sig. ρ Sig. ρ Sig. Ambivalent Sexism Inventory Hostile -0.048 0.551 -0.049 0.541 0.024 0.764 -0.053 0.508 Anti-Feminism -0.119 0.136 -0.116 0.145 0.010 0.904 -0.170 0.032 Heterosexual Intimacy 0.026 0.747 0.008 0.919 0.061 0.442 -0.053 0.510 Protective Paternalism -0.042 0.596 -0.033 0.679 0.047 0.559 -0.111 0.166 Comp. Gender -0.126 0.114 -0.124 0.119 0.034 0.672 -0.165 0.038 Differentiation Modern Sexism Scale

Against „Special 0.062 0.437 0.060 0.453 0.051 0.520 0.031 0.698 Treatment‟ Equality Attained 0.019 0.815 -0.011 0.888 0.085 0.286 -0.045 0.577 Sexual Beliefs Scale

Token Resistance -0.138 0.082 -0.141 0.077 0.000 0.996 -0.101 0.205 Leading On Justifies Force 0.058 0.464 0.010 0.902 0.175 0.028 0.042 0.596 Women Like Force -0.075 0.349 -0.077 0.337 0.022 0.782 -0.075 0.349 Men Should Dominate -0.128 0.107 -0.112 0.159 0.022 0.778 -0.168 0.034 No Means Stop -0.056 0.485 0.012 0.882 -0.219 0.006 0.006 0.936 1 Bold indicates significance at p < 0.1

There was a weak tendency for respondents with higher levels of average use of danger slang terms for the male genitals to score higher on the Leading On Justifies Force scale and lower on the No Means Stop scale (Table 22). In other words, higher use of danger slang terms for the male genitals correlated with higher levels of agreement that „leading on a man sexually justifies him using force‟ and lower levels of agreement that „saying no in a sexual encounter means stop.‟

To summarize, the majority of significant correlations were related to the danger category‟s variables (Table 22). Higher levels of use of danger slang terms for the male genitals correlated with higher levels of belief that the use of force by men is acceptable in sexual encounters. Higher levels of perceived offensiveness to danger slang terms correlated with lower levels of sexism.

Female Genital Slang Term Categories

There were 31 of 324 significant correlations at the p < 0.1 level between the slang category variables for the female genitals and the sexism subscales while controlling for the demographic variables (see Tables 23, 24, and 25 and Appendices R, S, and T). By controlling for demographic variables, 12 of the correlations from hypothesis 3 remain significant, 19 lost significance, and 19 gained significance. Though these 31 significant correlations are approximately what would be expected by chance, they were not spread across the categories equally. The majority of the significant correlations were within the danger, nonsense, and

“cunt” categories.

The danger category variables for female genital slang terms contain nearly one third of the significant correlations seen in Table 23. The number of danger terms listed correlated with

five sexism subscales. There was a weak tendency for respondents who listed more danger slang terms for the female genitals to score lower on the Hostile, Heterosexual Intimacy, Protective

Paternalism, and Token Resistance scales and higher on the No Means Stop scale. Furthermore, respondents who had danger slang terms comprise a higher percentage of the total number of slang terms listed for the female genitals weakly tended to have lower scores on the Hostile and

Token Resistance scales. There was a weak tendency for respondents with higher levels of average use of danger slang terms for the female genitals to score lower on the Token Resistance and Leading On Justifies Force scales. Last, there was a weak tendency for participants with higher levels of perceived offensiveness to listed danger terms for the female genitals to score lower on the Token Resistance scale. In sum, the knowledge, use, and perceived offensiveness to danger slang terms for the female genitals correlated negatively with sexism.

Table 23: Partial Correlations and Significance Values Between Danger Category Variables for Female Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Danger (♀)

Number Percent Avg. Use Avg. Off.

ρ Sig. ρ Sig. ρ Sig. ρ Sig.

Ambivalent Sexism Inventory Hostile -0.156 0.050 -0.146 0.066 -0.116 0.146 -0.015 0.856 Anti-Feminism -0.013 0.874 0.010 0.899 -0.031 0.698 0.019 0.816 Heterosexual Intimacy -0.155 0.050 -0.124 0.119 -0.103 0.197 -0.079 0.320 Protective Paternalism -0.136 0.087 -0.115 0.150 0.041 0.604 -0.110 0.168 Comp. Gender -0.062 0.437 -0.041 0.611 -0.104 0.193 0.052 0.514 Differentiation Modern Sexism Scale

Against „Special 0.032 0.690 0.027 0.738 0.056 0.483 -0.017 0.835 Treatment‟ Equality Attained -0.047 0.558 -0.012 0.882 0.110 0.166 -0.133 0.094 Sexual Beliefs Scale

Token Resistance -0.186 0.019 -0.147 0.065 -0.183 0.021 -0.156 0.050 Leading On Justifies Force -0.036 0.654 -0.053 0.505 -0.148 0.062 -0.013 0.873 Women Like Force -0.084 0.295 -0.038 0.636 -0.092 0.249 0.002 0.979 Men Should Dominate -0.107 0.181 -0.106 0.185 -0.088 0.271 0.005 0.946 No Means Stop 0.139 0.080 0.120 0.131 0.122 0.127 0.088 0.272 1 Bold indicates significance at p < 0.1 * Partial correlations impossible because Average Use = 0 for all 175 cases

There were six significant correlations out of 48 total correlations between the variables in the nonsense category and the sexism subscales (Table 24). Respondents who listed more

nonsense slang terms weakly tended to score higher on the Protective Paternalism scale.

Similarly, respondents who had nonsense slang terms comprised larger percents of all the terms listed for the female genitals weakly tended to score higher on the Protective Paternalism scale.

There was a weak tendency for respondents with higher levels of average use of nonsense terms for the female genitals to score higher on the Heterosexual Intimacy, Protective Paternalism,

Complementary Gender Differentiation, and Equality Attained scales. To summarize, the knowledge and use of nonsense slang terms for the female genitals significantly correlated with increased levels of sexism.

Table 24: Partial Correlations and Significance Values Between Nonsense Category Variables for Female Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Nonsense (♀)

Number Percent Avg. Use Avg. Off.

ρ Sig. ρ Sig. ρ Sig. ρ Sig.

Ambivalent Sexism Inventory Hostile 0.046 0.565 0.030 0.705 0.124 0.120 0.035 0.658 Anti-Feminism -0.103 0.195 -0.100 0.211 0.035 0.661 -0.049 0.542 Heterosexual Intimacy 0.113 0.157 0.066 0.405 0.164 0.039 0.046 0.561 Protective Paternalism 0.148 0.063 0.137 0.085 0.146 0.067 0.073 0.361 Comp. Gender 0.056 0.481 0.035 0.660 0.137 0.085 0.101 0.206 Differentiation Modern Sexism Scale

Against „Special -0.025 0.752 0.022 0.783 0.069 0.384 0.092 0.248 Treatment‟ Equality Attained 0.001 0.992 0.040 0.616 0.158 0.046 0.063 0.431 Sexual Beliefs Scale

Token Resistance -0.017 0.828 -0.022 0.779 0.082 0.306 -0.072 0.367 Leading On Justifies 0.074 0.356 0.070 0.381 0.015 0.848 0.052 0.517 Force Women Like Force -0.028 0.729 -0.027 0.737 0.082 0.305 -0.069 0.385 Men Should Dominate -0.066 0.407 -0.058 0.470 -0.079 0.322 -0.096 0.228 No Means Stop -0.003 0.971 0.039 0.628 0.032 0.689 -0.003 0.967 1 Bold indicates significance at p < 0.1

By controlling for demographic characteristics, the number of significant correlations with the “cunt” category‟s variables dropped from 10 in hypothesis three to 6 (see Tables 18 and

24). The act of listing the word cunt as a term for the female genitals correlated weakly with lower scores on the Against „Special Treatment‟ and Equality Attained scales from the Modern

Sexism Scale (Table 25). Similarly, there was a weak tendency for respondents with higher

values of perceived offensiveness to the term “cunt” to score lower on the Against „Special

Treatment‟ and Equality Attained scales. However, there was a weak tendency for respondents with higher reported values of use of the term “cunt” to score higher on the Token Resistance and Leading On Justifies Force scales and to score lower on the No Means Stop scale. In sum, listing the word cunt and finding it offensive was correlated with lower levels of modern sexism.

But higher levels of use of the word cunt correlated with increased agreement that „women often say no when they mean yes in sexual situations,‟ that „leading on a man sexually justifies him using force,‟ and lower agreement with „saying no in a sexual situation means stop.‟

Table 25: Partial Correlations and Significance Values Between Listing of “Cunt”, Use of “Cunt”, and Perceived Offensiveness to “Cunt” and Sexism Scale Subscales (N = 175)1 “Cunt” Listed* Use Offensiveness ρ Sig. ρ Sig. ρ Sig. Ambi valent Sexism Inventory Hostile 0.015 0.848 0.104 0.191 0.015 0.854 Anti-Feminism -0.069 0.389 0.058 0.465 -0.121 0.130 Heterosexual Intimacy -0.013 0.868 0.082 0.304 -0.060 0.450 Protective Paternalism -0.029 0.715 0.019 0.808 -0.069 0.387 Comp. Gender -0.077 0.332 -0.047 0.553 -0.057 0.479 Differentiation Modern Sexism Scale

Against „Special -0.146 0.067 0.006 0.938 -0.136 0.088 Treatment‟ Equality Attained -0.165 0.038 0.044 0.583 -0.169 0.033 Sexual Beliefs Scale

Token Resistance 0.039 0.627 0.137 0.085 0.059 0.457 Leading On Justifies Force -0.052 0.515 0.172 0.030 -0.041 0.604 Women Like Force -0.031 0.703 0.103 0.194 -0.025 0.757 Men Should Dominate -0.040 0.618 0.087 0.274 0.025 0.757 No Means Stop -0.074 0.351 -0.147 0.064 -0.053 0.509 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

To summarize, the knowledge, use, and perceived offensiveness to slang terms for the female genitals that frame sex as danger was correlated with lower levels of sexism. However,

the knowledge and average use of nonsense slang terms for the female genitals correlated with higher levels of sexism. Last, listing and being offended by the word cunt was negatively correlated with modern sexism (the belief that sexism is no longer a problem and that policies to address sexism are discriminatory of men). But using the word cunt was positively correlated with Sexual Belief Scale (a rape-myth acceptance scale) subscales, specifically subscales dealing with saying “no” in a sexual encounter and men using force.

DISCUSSION

An unanticipated finding of this research was the degree to which respondents listed medical terms, non-genital terms, and altogether inaccurate terms for the genitals. Of the 512 unique terms listed for the genitals, 43 (8.4%) were not slang terms for the genitals (or not of the sex asked for). The context in which a term like “shaft” is used may make the difference between medical and slang in the mind of its user. Furthermore, the use of medical terms in other colloquialisms, such as “getting head” when referring to receiving fellatio, may blur the lines between medical and slang terms. Future research may wish to explore this apparent overlap in terms considered both medical and slang.

The similar number of unique slang terms for male and female genitals (N = 233 and N =

236, respectively) was unexpected. However, judging by the N‟s for the top 10 slang terms for both male and female genitals, there appears to be more variation among the slang vocabularies for the female genitals. Just as Grossman and Tucker (1997) found, there is a significant difference at the p < 0.05 level in the means of the average use and average offensiveness between genital terms for the male and female genitals. The mean of the average use for female

genital terms was significantly lower than the mean of the average use for male genital terms.

Conversely, the mean of the average offensiveness for female genital terms was significantly higher than the mean of the average offensiveness for male genital terms. However, it is unclear if this difference is due to the more abject nature of the terms for the female genitals as

Grossman and Tucker (1997) suggested. Though it was not the goal of this study to address it, this difference in use and offensiveness between male and female genital terms warrants further investigation.

Lastly, the study identified a distinct lack of authority slang terms for the female genitals, which is not surprising given prior research. However, Naugler (2009) found numerous examples of authority slang terms for the breasts. Her argument parallels slang terms for the breast and for the penis. Naugler argues that breasts are the authenticators of femininity; the presence of breasts is a primary outward bodily indicator of womanhood. Just as the penis is for men, the larger the breasts are, the more feminine the woman is. Naugler‟s assertion is corroborated by the distinct lack of authority slang terms for the female genitals.

Due to the exploratory nature of this study, and the relatively small sample size, a significance value of p < 0.1 was chosen. This more generous level of significance allows us to home in on potentially fruitful areas for future research. However, it may also result in more false positives than in other studies, so all findings should be considered in light of this fact.

Hypothesis 1: Demographic characteristics have significant effects on slang knowledge, use, offensiveness, and categories.

When we take into consideration that with p < 0.1 roughly 10% the coefficients will be significant by chance, a few patterns emerge from the significant coefficients (see Tables 6

through 10 and Appendices E through H). First, gender significantly impacts the slang variables

(excluding the category variables danger, authority, abject, euphemism, nonsense, euphemism+nonsense, and “cunt”) for the male genitals (see Table 6). Men listed significantly larger numbers of terms for the male genitals and listed significantly larger numbers of actual slang terms for the male genitals than women did. Men also had higher levels of average use and had lower levers of variance in perceived offensiveness when compared to women. However, gender does not cause any significant differences in the female genital slang variables (excluding the category variables danger, authority, abject, euphemism, nonsense, euphemism+nonsense, and “cunt”) beyond what we might expect at random (see Table 7).

The findings corroborate the results of previous studies that gender does significantly impact the knowledge of slang. However, this study only supports that claim with regards to male genital terms. There were no significant gender differences in the production of female genital terms except for the nonsense and euphemism+nonsense categories. Though the reasons behind these findings are not immediately clear, I suspect that there is more exposure to and acceptance of genital slang terms by both men and women than in the past. This may also be due to the sample; college students may share a larger vocabulary regardless of gender.

Gender was particularly significant in the category variables for female genital slang terms. Men tended to know and use more abject slang terms for the female genitals, whereas women tended to know and use more euphemistic and nonsense slang terms and found those terms less offensive. This use of more euphemistic language by women than used by men is in line with the sociolinguistics research discussed earlier. One explanation is that the use and decreased perceived offensiveness to the nonsense slang terms reflects an in-group bias, similar to the findings of Ernster‟s (1975) study of menstruation terms. In other words, these terms may

be “girl speak” and meant to be understandable only to other women. Another, in my opinion more plausible, explanation is that women experience their bodies indirectly (i.e. through the male gaze (Mulvey 1975)) and this language use reflects that indirect relationship.

Two categories contained more significant findings than would be expected by chance: authority terms for the male genitals and the “cunt” category (see Table 8 and 11). For the authority category for male genital slang, the primary influence appears to be age (see Table 8).

Years in school and traditional student status are both significantly correlated with age of the respondent. Mother‟s education also was significant for the number of terms listed and average offensiveness. Overall, the older you are, the less likely you are to list authority slang terms or find them offensive. The reasons for these findings are not clear.

The “cunt” category contained 5 significant coefficients, 2 more than what would be expected by chance (see Table 11). Men are more likely to list and use “cunt.” Higher levels of mother‟s education increases the likelihood “cunt” will be listed, but also increases the perceived offensiveness of the term. It does appeal to common sense that men would be more likely to know and use the term cunt, especially given its emotional weight. This also makes sense with the findings by sociolinguists that men use dysphemisms more frequently than women.

Overall out of the demographic variables, gender plays the largest role in affecting genital slang knowledge, use, and perceived offensiveness. The findings conditionally corroborate past research, however the influence of gender may be waning as time advances and the linguistic spheres of men and women further merge.

These findings in support of hypothesis 1 are not surprising. Given research on language with respect to other demographic characteristics, the importance of these variables is expected.

Though characteristics such as SES is sometimes difficult to measure in teens and young adults

(e.g., Wardle, Robb, and Johnson 2002), any future research regarding slang would be prudent to consider and control for demographic variables beyond sex/gender.

Hypothesis 2: Demographic characteristics have significant effects on sexism.

The findings in hypothesis 2 were overall as expected. Men tend to be more sexist on a variety of measures. Racially self-identifying as black was correlated with higher levels of

“benevolent” sexist beliefs and lower acceptance of two rape-myth subscales. Despite the prevalence of hostile or overt sexist beliefs decades ago, age was significant for only one sexism subscale. Higher levels of mother‟s education correlated with lower levels of sexism on all three scales, including both subscales of the Modern Sexism Scale.

Two results from hypothesis 2 were intriguing however. First, the existence of what I called the “Anti-Feminism” subscale in the Ambivalent Sexism Inventory and the two subscales that I called “Equality Attained” and “Against Special Treatment” on the Modern Sexism Scale was made clearer. Higher levels of educational attainment by respondents correlated with lower levels of the Anti-Feminism and Equality Attained subscales. I suspect this is due to increased exposure to feminist theories and progressive thought in the course of their education. However, the reverse could be true; openness to feminist theories and progressive thought may make one prone to seek higher education and attend sociology classes.

Second, being straight (heterosexual) correlated with significantly higher scores on the

Ambivalent Sexism Inventory and the Sexual Beliefs Scale. This makes sense given that both scales relate to relationships between men and women. The Ambivalent Sexism Inventory is based on the idea that the simultaneous necessity of relationships and the power differentials

between men and women cause ambivalent attitudes toward women and men. Thus the contrapositive (i.e., if not p, then not q) that non-heterosexuals do not have ambivalent attitudes toward men and women makes logical sense. Similarly, the Sexual Beliefs Scales focuses entirely on sexual relations between men and women. By being outside that framework, non- heterosexuals do not necessarily buy into the rape mythology. In sum, measuring attitudes toward gender norms and sex(ual intercourse) norms of lesbigay individuals may become problematic due to their potentially non-heteronormative beliefs. Future research may wish to edit existing scales to minimize or create new scales that address these problems.

Hypothesis 3: Slang knowledge, use, offensiveness, and categories are significantly correlated with sexism.

The purpose of hypothesis three was to see if there were any significant correlations between slang and sexism. Their presence gives us all the more reason to control for the various demographic variables in hypotheses 1 and 2 in order to minimize spurious relationships.

However the lack of any significant correlations does not mean controlling for demographic variables would be futile. On the contrary, comparing the correlations from hypotheses 3 and 4 allows us to see which relations were spurious and which were not significant due to a suppression effect. As discussed earlier, there were a number of significant correlations found, but these correlations may be misleading. Thus we must examine the results from hypothesis 4 where I controlled for the potentially confounding variables.

Hypothesis 4: Slang knowledge, use, offensiveness, and categories are significantly correlated with sexism while controlling for demographic characteristics.

Significant findings in support of hypothesis 4 are numerous and some are unexpected and even confusing. Some of these correlations elude simple explanation.

One of the most significant findings is that the average use of genital terms for both the male and female genitalia positively correlates with a number of sexism scale subscales. This finding corroborates the suggestion by previous scholars that the terms we use for the genitals are sexist in nature and may lead to, and/or reflect sexist beliefs. However, there are two important caveats to make. First, it is the use of these terms more than the knowledge of them that is correlated with sexism. Use of particular language can be due to conscientious choice or passive (non-thinking) acceptance. Either the user of these slang terms agrees with the patriarchy and sexist beliefs they represent or the user does not challenge them. The second point is that the causal order is not suggested by these findings. Thus, in the case of conscientious choice, the sexist attitudes may precede the choice to use these terms, as opposed to the terms causing sexism in their user. It seems likely to me that both causal orders are possible; those who are sexist may seek out terms to use that reflect their beliefs and constant exposure (and the subsequent embedding of them in the forefront of one‟s memory) may cause their user to experience gender and sexual relations through these sexist-tainted words.

Regardless, the relationship most certainly is reciprocal in nature, causing a sexism feedback loop.

Another intriguing finding is that the average use-offensiveness interaction term, especially for the male genital terms, correlated with sexism on a number of subscales. This

variable measures simultaneously high levels of use and perceived offensiveness to genital terms.

I originally created this variable because it struck me as odd that some respondents indicated high levels of use of a term while finding that same term highly offensive. Though I am not sure why this correlates so consistently with sexism, it seems that the existence of these high scores reflects some type of cognitive dissonance or deliberate use of dysphemisms. The former idea suggests that these terms maintain an ambivalent state in the minds of their users. One way to reduce cognitive dissonance is to alter one of the cognitions to create consonance. This could play out in three scenarios:

1. Levels of sexism have increased, thus levels of use increase to reflect these newly

formed attitudes. However, perceived offensiveness remains stable (high).

2. Levels of use have increased perhaps due to their use by role models or peers (e.g.,

joining a fraternity) (for an example of this, see Labov 1972), causing levels of

sexism to increase. However, perceived offensiveness remains stable (high).

3. Levels of sexism have increased and levels of offensiveness increase (perhaps due

to insulting the phallus, as mentioned above). However, use remains stable (high)

due to habit.

I find scenarios 2 and 3 most compelling, due to their plausibility among undergraduates. It is not certain what mechanisms are causing the findings, but it is clear that simultaneously high levels of use and perceived offensiveness are correlated with sexist attitudes.

The danger slang category seems paradoxical and contrary to the findings for the other slang categories. Unlike the rest of the male genital slang category variables, finding danger slang terms offensive correlated with lower levels of sexism. Finding terms that frame sex as a

dangerous or violent act logically correlates with lower levels of sexism and lower levels of acceptance of rape myths. Similarly, actually using these terms would logically correlate with high levels of sexism and acceptance of rape myths. However, listing danger terms for the male and female genitals were also correlated with lower levels of sexism, especially in the

Ambivalent Sexism Inventory and the Sexual Beliefs scale. Why simply knowing terms like

“ramrod” or “man stealer” would correlate with lower levels of these particularly dangerous forms sexism is unclear and warrants further investigation. Even more confusing is why the use of danger slang terms for the female genitals was correlated with lower levels of sexism. It appears that use of these terms rejects the stereotypes of the sexually passive female and sexually aggressive male. However, most of the danger terms for the female genitals relate to passive dangers such as traps (see Appendix D) and thus reflects the passive female stereotype.

The findings in the nonsense slang category for the female genitals lend credence to the argument that obfuscating the genitals is deleterious to the attitudes toward sex and gender.

Though knowledge of euphemistic terms for the female genitals was negatively correlated with the Protective Paternalism subscale of the Ambivalent Sexism Inventory, the knowledge and especially the average use of nonsense slang terms was positively correlated with various sexism scale subscales. These correlations are mostly among the “benevolent” subscales of the

Ambivalent Sexism Inventory. The issue here may be the intent of the nonsense slang terms.

While the nonsense slang terms obfuscate the genitals like euphemisms do, they can also be fun, humorous, and absurd. Making light of the female genitals may be a rejection of the cliché that they are filthy, dangerous, or nasty. This may seem like a positive thing, but it seems that instead of seeing them for what they are (just genitals), the nonsense terms cause (or are caused by) benevolent sexism beliefs.

Last, we come to one of the most emotionally loaded words in the English language: cunt.

Knowing this term and finding it offensive are positively correlated with lower levels of modern sexism. In my opinion, the causal order here is most likely that sexism is antecedent to the slang variables. That is to say, lower levels of modern sexism means that a person recognizes that gender inequality remains pervasive in our society. This awareness is probably linked to awareness of gender issues as a whole, and thus awareness of the term “cunt” and its power.

Average use of the word “cunt” was correlated with higher acceptance of rape myths.

Specifically, the more someone uses the word “cunt,” the more they believe that women offer token resistance to sexual advances, that the men who are sexually led on by women are justified in using force, and that saying no during a sexual encounter does not necessarily mean stop.

Taken at face value, these correlations to rape-myth acceptance are quite worrisome, though the causal mechanism is not clear. There is something particular about the use of the word “cunt” that correlates with these beliefs, independent of age, gender, etc.

Conclusion

The data corroborate all four hypotheses. Knowledge, use, and perceived offensiveness of genital slang terms significantly varied by demographic characteristics. Subscales created from three sexism scales significantly varied by demographic characteristics. The genital slang variables correlated significantly with a number of sexism scale subscales. Some of these correlations disappeared while controlling for the demographic variables, but others became or remained significant. The only demographic variable that was not significant on any regressions and correlations was the traditional student dummy variable.

Any future research regarding genital slang, or slang in general, would do well to measure and consider the relationship of demographic characteristics with language. In addition to gender, race, education, and SES are important to measure. This study was limited in its measure of SES and future researchers are advised to carefully consider the difficulty of measuring it in a group that has not yet established its own SES. Furthermore, other demographic variables such as religion, religiosity, marital/relationship status, and childhood household makeup may be of interest in future research.

Slang does correlate with sexist attitudes, but sometimes in unpredicted and surprising ways. In particular, the use of male and female genital slang terms is positively correlated with sexism, especially female genital slang terms. Additionally, high levels of use of male genital slang terms that the user finds offensive is significantly correlated with parts of the Ambivalent

Sexism Inventory and the Sexual Beliefs Scale. For the male genitals, use of slang terms that framed the genitals as dangerous or violent correlated with higher levels of sexism, especially rape myth acceptance. Furthermore, finding those danger slang terms offensive correlated with lower levels of sexism. However, knowledge, use, and perceived offensiveness to female genital slang terms that frame the genitals as dangerous or violent were all correlated with lower levels of sexism. Last, higher levels of nonsensical female genital slang terms correlated with higher levels of sexism. This paper proposed some suggestions as to the causal mechanisms behind the correlations, but more in-depth research may be able to elucidate them. Qualitative analyses would be well equipped to delve into the intertwined and reciprocal nature of the connection between slang and sexism.

Language has the power to shape our realities. The genitals are at a nexus of taboo, sexuality, and symbolism. The terms we use to refer to them reflect both individual and cultural

beliefs about sex and gender. The symbols and images imbedded in these words evoke the patriarchy and sexism that permeates our culture. This research suggests that the frequent use of slang terms for the genitals, especially the word cunt, correlates with sexist beliefs. Further study of sexual slang terms will help us to understand how language connects the individual to the social structure and the sexual stereotypes of our culture.

Footnotes

1 “Euphemism” refers to using less offensive words or phrases in place of something offensive or objectionable. “Dysphemism” is the antonym of euphemism; it is the use of offensive words or phrases in place of something relatively inoffensive or unobjectionable. (Paraphrased from definitions on http://www.merriam-webster.com/).

2 Named after philosopher René Descartes, the Cartesian mind-body dichotomy is the belief that the mind and body are separate and essentially mutually exclusive. The body is a vessel which the body occupies; the functions of the body are incidental to the needs of the mind (Bordo 1999).

3 During the 2009-2010 academic year, students in the University of Cincinnati‟s McMicken

College of Arts and Sciences (home to the sociology department) were 53.4% female and 46.6% male. The breakdown of racial categories for this group of students was 71.2% white, 12.2% black or African American, 1.8% Hispanic, 3.3% Asian, 0.2% American Indian, 0.1% multiracial, 5.1% non-resident, and 6.1% unknown. (Source: http://www.artsci.uc.edu/collegemain/news/annual_report/ar0910/diversity.aspx) Of course, sociology classes may also include students from outside the College of Arts and Sciences.

4 In the section of the survey where participants listed terms for the male genitals, this participant listed “num[sic]-nuts” as well as the term “nuts.” Because of this, I deemed “num-nuts” a non- slang term.

5 Choice of terms referring to the strength of relationships between variables (e.g., weak, strong) were guided by Pett et al. 2003. Correlations between 0.00 and 0.29 are described as “weak,” between 0.30 and 0.49 are described as “low,” between 0.5 and 0.69 are described as

“moderate,” between 0.7 and 0.89 are described as “strong,” and between 0.9 and 1.00 are described as “very strong” (Pett et al. 2003:60).

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88 Appendix A: List and Frequency of All Male Genital Terms Listed1

Terms N Terms N Terms N Terms N Terms N

Anaconda 3 Dong 14 Lollipop 2 Peter 19 Stuff 1

Baby Crem* 1 Down There 1 Long John 2 Peyton Manthing 1 Sug 1

Baby Maker 3 Driving Stick 1 Magic Stick 11 Piece 2 Swang 2

Bag O' Fun 1 D-Stick 1 Main Vein 2 Ping Pong Balls 1 Sword 3

Balls 134 Family Jewels 4 Mamba 1 Pipe 7 Tag Along 1

Ballsack 12 Fellas 1 Man Business 1 Pisser 1 Taint** 2

Banana 1 Flesh Arrow 1 Man Man 1 Poker 1 Tallywacker 8

Bat 2 Fly Swatter 1 Man Meat 2 Pole 15 Tea Bag 1

Bat Wing 1 Fools 1 Man Parts 2 Pool Stick 1 Team 1

Beefstick 1 Foot Long 1 Mandingo 2 Pork 1 Tenders 1

Big Boy Toy 1 Friend 1 Manhood 2 Pork Sword 1 Testicles** 5

Big Daddy 1 Front 1 Marbles 2 Prick 7 Testies** 3

Big Guy 1 Fuck Stick 4 Meat 11 Prince 1 The Boys 1

Bishop in a Turtle Neck 1 Fuzzy Squirrel 1 Meat and Potatoes 1 Privates 5 The Brain 1

Boi 1 Giggle Berries 1 Meat and Two Veg 2 Pube Steak 1 The Children 1

Bolts 1 Giggle Stick 1 Meat Stick 2 Pubes 1 The Goat 1

Boner 5 Gonads** 5 Meatwad 1 Purple Headed Yogurt Slinger 4 The Log 1

Boner Place 1 Gooch** 2 Member 12 Purple Helmet 2 The Snake Charmer 1

Boys 3 Goods 1 Mr. Happy 2 Python 2 Thick 1

Brain 1 Grapes 2 Mushroom Head 1 Rail 1 Thing 2

Brawtwurst 1 Gun 1 My Men 1 Ramrod 1 Thingy 2

Broom 1 Hammer 1 Nads 5 Remote 1 Third Leg 2

Buddy Whack-st* 1 Hang Dang 1 Nards 1 Richard Gere 1 Ting 1

Butch 1 Hang Down 3 Needle Dick 2 Rock 1 Toilet Seat Slapper 1

Cajones 1 Hangers 1 Neiner 1 Rocket 5 Tool 1

Appendix A: List and Frequency of All Male Genital Terms Listed1 (Continued) Terms N Terms N Terms N Terms N Terms N

Camel Tail 1 Head** 5 No-No Parts 1 Rod 16 Tripod 1

Cash and Prizes 1 Him 1 Numb Nuts** 1 Rod and Reel 1 Trouser Snake 4

Choch 1 Hotdog 4 Nut Sack 5 Rope 1 Turk 1

Chode 9 Huevos 1 Nuts 54 Sack 38 Turtle 1

Cock 93 Hymen Hammer 1 Olives 1 Satchel 1 Twig and Berries 4

Cock Meat 1 Jack 1 One-Eyed Lizard 1 Sausage 6 Twinkie 1

Cock Meat Sandwich 1 Jacking Off Buddy 1 One-Eyed Monster 4 Schlong 26 Two Peas in a Pod 1

Coconuts 1 Jewels 15 One-Eyed Purple Monster 1 Scrote* 2 Vagina** 1

Coin Purse 2 Jibblens 1 One-Eyed Snake 1 Scrotum** 2 Vive (rhymes with sleeve) 1

Crawl the Warrior King 1 Jimmy 4 One-Eyed Willy 1 Shaft** 23 Wacker 1

Crotch 3 Jizz Machine 1 Pack 1 Shit 1 Wang 18

Crow 1 Jock 1 Package 19 Shooter 1 Wanker 3

Crown Jewels 1 John 3 P-Bob 1 Slong 6 Wee Wee 10

Dang a Lang 1 Johnson 30 Peach Cleaver 1 Snake 8 Weenie 6

Danny Woodhead 1 Juan Pedro 1 Peanut(s) 2 Snicker 1 Weenis 1

Dice 1 Junk 34 Pecker 17 Spanky 1 Whizzer 1

Dick 161 King and His Jewels 1 Pee Pee 16 Spear 1 Wiener 60

Ding a Ling 9 Kit Kat 1 Pee Shooter 1 Special Place 1 Willy 7

Ding Dong 5 Knob 2 Peen 2 Special Purpose 1 Winky 2

Dinker 1 Little [Insert Man's Name] 3 Peenie 1 Staff 1 Wood 5

Dinky 1 Little Guy 2 Peep 2 Stick 18 Woody 4

Disco Stick 3 Little Man 2 Pen 1 Stiffy 2 Wrinkle Stick 1

Dog 1 Little Richard 1 Pencil Dick 1 Stinger 1 Yogurt Slinger 1

Dome* 1 Lizard 3 Penis** 27 Stones 1 1 Various spellings grouped and standardized * Difficult to decipher on original survey ** Deemed a non-slang term for the male genitals

Appendix B: List and Frequency of All Female Genital Slang Terms Listed1 Terms N Terms N Terms N Terms N Terms N Ass Preview 1 Coochie 14 Hoo-ha 10 Old Man in a Sail Boat 1 Tats** 1 Ass** 1 Cookie 2 Hoo-Hoo 1 One-Eyed Thing 1 Tenders 1 Axe Wound 1 Coot 1 Hootchie-Coo 1 Ovaries** 2 Thang 2 Baby Box 1 Cooter 20 Hot Button 1 Oyster 1 The Bean 1 Baby Cannon 1 Core 1 Hot Spot 1 Peach 3 The Box 1 Baby Maker 10 Cotton Candy 1 Hotdog Bun 1 Pearl 2 The Button 1 Bean 4 Cow Tongues 1 Human Hamburger 1 Pee Pee 2 The Goods 1 Bearded Axe Wound 1 Crotch 9 Important Lips 1 Pie Hole 1 The Hole 1 Bearded Clam 1 Cuchy 1 J-J 1 Pikachu 1 The Misses 1 Beaver 9 Cum Dumpster 3 Jugs** 3 Pink 4 The Pearl 1 Bee Hive 1 Cunt 106 Juice Box 3 Pink Taco 2 The Trap 1 Beef Curtains 2 Curtain 1 Ka Pichachoo 1 Piss Flaps 1 Tits/Titties** 12 Betty 1 Dick Sharpener 1 Kill 1 Pleasure Zone 1 Trap 1 Bird 1 Dirty Cunt Hair 1 Kitty 8 Pocket Book 1 Trim 1 Black Hole 2 Dirty Taco 1 Kitty Cat 9 Poe Poe 1 Tuna 1 Blood Box 1 DNA Dumpster 1 Kooka 6 Pooka 1 Tuna Taco 1 Blossom 1 Douche** 1 Kootch 1 Poontang 1 Twang 1 Boobs/Boobies** 7 Down There 2 Kuder 1 Pooter 1 Twat 34 Box 15 Egg Sack 1 La Vagine 1 Pork Steeple** 1 Twins** 1 Breasteses** 1 Eggs** 1 Labe 1 Pot of Gold 1 V 3 Breasticles** 1 Elephant Ears 1 Lady Area 1 Pouch 1 Va Gi Gi 1 Breasts** 2 Emerald Triangle 1 Lady Business 1 Privates 5 Vag/Vaj/Vadge 64 Bubblegum 1 Eye 1 Lady Junk 1 Punani 2 Vagina** 20 Bush 7 Fatty 1 Lady Parts 4 Pune 1 Vagine/Vajean 6 Butt*/** 1 Female Part 1 Lady Region 1 Punni 1 Vagoo 1 Button 1 Fish Food 1 Lily Pad 1 Puss 3 Va-Jay-Jay 63 Camel Toe 3 Fish Market 1 Lips** 28 Pussy 148 Vajja 1 Cans** 1 Fish Taco 6 Locnus 1 Puzinga 1 V-Badge 1 Carpet 2 Flap(s) 2 Love Below 1 Rabbit Hole 1 V-Box 1 Cash-n-Prizes 1 Flower 3 Love Hole 1 Rack** 1 Velvet Wallet 1 Cat 5 Front 1 Love Land 1 Roast Beef 3 Ver Jay Jay 1 Causlopus 1 Front Butt 2 Lovely Lips 1 Roast Beef Curtains 2 Vertical Stripe 1 Cave 2 Front Door 1 Lower Mouth 1 Roast Beef Sandwich 1 V-Gee 1 Cavern 1 Fuck Hole 1 Lube Tube 1 Sarah 1 Vive Garage 1

Appendix B: List and Frequency of All Female Genital Slang Terms Listed1 (Continued) Terms N Terms N Terms N Terms N Terms N Cha Cha 1 Fun Box 1 Man Eater 1 Sausage Wallet 1 V-JJ 1 Chach 3 Fun Button 1 Man in a Boat 1 Shag Carpet 1 Volcano 1 Cherry(ies) 4 Fur Burger 2 Man Stealer 1 Shrimp 1 Waffle 1 Chesticles** 1 Garage 6 Meat Curtain(s) 4 Slip-N-Slide 1 Wahoo 1 Chick 1 Gash 1 Meat Pocket 1 Slit 7 Waste Basket 1 China 1 Gina 3 Meat Wallet 1 Slot 3 Waterfall 2 Clam 5 Gine 1 Melons** 4 Smashbox 1 Wee Wee 1 Clint 1 Glory Hole 1 Milk Shake** 1 Smelly 1 Wet 1 Cliq 1 Glove 1 Mitt 1 Snatch 27 Wet Wet 6 Clit 40 Goochie 1 Monkey 1 Snitch 1 Whisker Biscuit 1 Clitdick 1 Goodies 7 Monster 2 Soft Place 1 Whispering Eye 2 Clitori 1 Gorillas** 1 Moose Knuckle 1 Sperm Bank 1 Wiggles/Giggles 1 Clitoris** 2 G-Spot** 5 Mound 1 Split Knish 1 Wizard Sleeve 1 Cock Slot 1 Hairy Axe Wound 1 Muff 6 Squeeze Box 1 Womb** 1 Cock Sucker 1 Hairy Cyclops 1 Muffin 1 Squish Mitten 1 Wood Slot 1 Cock Wallet 1 Ham Wallet 1 Muffin Shop 1 Stinker 1 Wookie 1 Cock** 1 Her 1 Nana 1 Stuff 1 Coin Purse** 1 High School Curtains 1 Neden 1 Taco 12 Coin Slot 2 Hole 8 Nips** 2 Taint** 2 Cooch 16 Honey Hole 1 Nookie 1 Tatas** 2 1 Various spellings grouped and standardized * Difficult to decipher on original survey ** Deemed a non-slang term for the female genitals

Appendix C: Categorized Slang Terms for the Male Genitals1 Danger Authority Abject Euphemism Nonsense [Baseball] Bat Big Daddy Fools Crotch Dang-a-lang Flesh Arrow Bishop in a Turtleneck Jibblins [variant of giblets] Down There Ding-a-ling Fly Swatter Crawl the Warrior King Junk Front Ding Dong Gun King and his Jewels Meatwad Man Parts Dinker Hammer Little Richard One-Eyed Purple Monster Member Dong Hymen Hammer Long John [Silver] Shit No-No Part Niener Peach Cleaver Prince Package Swang Poker Richard Gere Piece Tallywhacker Pork Sword The Brain Privates Ting Prick Special Place Vive (rhymes with sleeve) Ramrod Special Purpose Wang Rocket Stuff Shooter Thingy Sword Stinger 1 Words in [ ] indicate words added by the author to elucidate meaning.

Appendix D: Categorized Slang Terms for the Female Genitals Danger Authority Abject Euphemism Nonsense Axe Wound Clint Ass Preview Core Cha Cha Nookie Baby Cannon Blood Box Crotch Chach Poe Poe Bearded Axe Wound Dirty Cunt Hair Down There Cooch Pooka Bee Hive Dirty Taco Female Parts Coocha Poontang Black Hole Fish Food Front Coochie Pooter Dick Sharpener Fish Market Front Door Coslopus Punani Gash Fish Taco Her Hoo-hah Pune Hairy Axe Wound Front Butt Important Lips Hoo-Hoo Punni Kill Hairy Cyclops Lady Area Hootchie-Coo Puzinga Man Eater Lady Junk Lady Business J-J Twang Man Stealer Monster Lady Region Ka Pichachoo Va Gi Gi Slit Shrimp Lady Parts Kooka Va-Jay-Jay Smashbox Smelly Love Below Locnus V-Gee (The) Trap Stinker Mound Nana Wahoo Volcano Tuna Privates Neden Whispering Eye Tuna Taco Soft Place Waste Basket Stuff Thang V

Appendix E: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Danger Categories for Male Genital Slang Terms Are Regressed on Demographic Variables (N = 175)1 Danger (♂) Number Percent Avg. Use Avg. Off. Independent Variables b Sig. b sig b Sig. b Sig. Constant -0.711 0.165 -0.081 0.194 -0.376 0.352 0.035 0.968 Sex (1 = male) 0.011 0.885 -0.002 0.836 0.068 0.273 -0.024 0.858 Age 0.012 0.385 0.002 0.263 0.000 0.986 -0.002 0.947 Straight* 0.058 0.734 0.011 0.607 0.062 0.644 -0.005 0.985 Black* -0.077 0.566 -0.007 0.655 -0.077 0.468 0.039 0.868 Other Race* -0.219 0.151 -0.022 0.225 -0.097 0.418 -0.338 0.203 Education 0.090 0.296 0.010 0.339 0.069 0.311 -0.045 0.765 Years In School 0.038 0.237 0.000 0.972 0.023 0.362 0.070 0.212 Traditional Student* 0.173 0.293 0.025 0.207 0.110 0.398 0.006 0.982 Parent #1‟s 0.018 0.557 0.003 0.394 -0.015 0.550 0.073 0.178 Education Parent #1‟s Occupational -0.001 0.769 0.000 0.362 0.001 0.584 -0.002 0.686 Prestige R2 0.047 0.037 0.033 0.031 Adjusted R2 -0.011 -0.022 -0.026 -0.028 F-Test 0.810 0.619 0.625 0.791 0.563 0.842 0.527 0.869 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Appendix F: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Abject and Euphemism Categories for Male Genital Slang Terms Are Regressed on Demographic Variables (N = 175)1 Abject (♂) Euphemism (♂) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off. Independent Variables b sig b sig b sig b sig b sig b sig b sig b sig Constant -1.274 0.013 -0.132 0.030 -1.668 0.237 -1.216 0.045 0.697 0.255 0.104 0.281 -0.022 0.985 -0.351 0.660 Sex (1 = male) 0.076 0.332 0.005 0.577 0.057 0.790 0.054 0.562 -0.216 0.022 -0.037 0.012 -0.157 0.392 -0.236 0.055 Age 0.018 0.200 0.002 0.262 0.026 0.503 0.030 0.076 -0.012 0.467 -0.002 0.437 0.006 0.845 0.037 0.093 Straight* 0.029 0.865 0.002 0.911 0.577 0.219 0.080 0.691 0.029 0.886 0.006 0.846 0.471 0.239 0.161 0.544 Black* -0.138 0.302 -0.017 0.277 -0.499 0.179 0.032 0.840 -0.029 0.857 0.005 0.838 -0.014 0.965 0.061 0.771 Other Race* 0.031 0.836 0.007 0.689 0.559 0.183 0.045 0.802 0.155 0.396 0.029 0.312 -0.092 0.796 0.072 0.760 Education 0.132 0.122 0.016 0.113 -0.076 0.748 0.012 0.909 0.080 0.436 0.008 0.605 0.207 0.303 -0.053 0.694 Years In School 0.053 0.102 0.003 0.393 0.133 0.134 0.044 0.254 -0.024 0.535 -0.005 0.382 0.011 0.888 -0.079 0.118 Traditional Student* 0.261 0.112 0.033 0.093 0.195 0.667 0.282 0.148 -0.185 0.346 -0.019 0.546 -0.136 0.725 0.168 0.513 Parent #1‟s Education -0.002 0.949 -0.002 0.665 -0.042 0.627 -0.021 0.571 -0.039 0.294 -0.006 0.333 -0.074 0.313 -0.020 0.685 Parent #1‟s Occupational 0.007 0.042 0.001 0.043 0.022 0.015 0.009 0.015 0.002 0.651 0.000 0.465 -0.005 0.537 0.003 0.511 Prestige R2 0.106 0.079 0.099 0.086 0.064 0.074 0.045 0.058 Adjusted R2 0.052 0.023 0.074 0.030 0.007 0.017 -0.014 0 F-Test 1.951 0.042 1.416 0.177 1.804 0.063 1.544 0.128 1.122 0.349 1.305 0.232 0.766 0.662 1.003 0.443 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Appendix G: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Nonsense and Euphemism+Nonsense Categories for Male Genital Slang Terms Are Regressed on Demographic Variables (N = 175)1 Nonsense (♂) Euphemism and Nonsense (♂) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off. Independent Variables b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. Constant -0.125 0.839 0.016 0.854 1.161 0.289 -0.874 0.377 0.572 0.503 0.120 0.331 1.139 0.480 -1.225 0.371 Sex (1 = male) 0.089 0.348 0.004 0.784 0.352 0.037 0.072 0.635 -0.127 0.330 -0.034 0.077 0.195 0.431 -0.164 0.434 Age 0.021 0.230 0.003 0.237 -0.006 0.847 0.042 0.125 0.008 0.729 0.001 0.797 0.001 0.989 0.079 0.037 Straight* -0.036 0.860 0.000 0.997 -0.275 0.451 0.221 0.504 -0.007 0.980 0.006 0.882 0.196 0.715 0.382 0.402 Black* 0.179 0.271 0.021 0.375 0.189 0.512 0.401 0.125 0.150 0.504 0.026 0.422 0.175 0.680 0.462 0.200 Other Race* -0.229 0.212 -0.031 0.243 -0.280 0.389 -0.288 0.329 -0.074 0.769 -0.002 0.951 -0.372 0.438 -0.215 0.597 Education -0.153 0.139 -0.024 0.112 -0.269 0.143 -0.235 0.159 -0.074 0.608 -0.016 0.449 -0.062 0.818 -0.287 0.212 Years In School 0.056 0.150 0.006 0.326 0.022 0.750 0.044 0.477 0.032 0.549 0.000 0.973 0.033 0.748 -0.035 0.689 Traditional Student* 0.308 0.122 0.051 0.081 0.305 0.386 0.448 0.160 0.122 0.656 0.032 0.422 0.169 0.744 0.617 0.163 Parent #1‟s Education 0.060 0.115 0.007 0.209 0.033 0.619 0.127 0.036 0.020 0.697 0.001 0.872 -0.041 0.680 0.108 0.199 Parent #1‟s Occupational -0.004 0.281 -0.001 0.073 -0.004 0.601 -0.005 0.448 -0.002 0.649 -0.001 0.459 -0.008 0.416 -0.001 0.869 Prestige R2 0.093 0.084 0.069 0.085 0.018 0.038 0.019 0.066 Adjusted R2 0.038 0.028 0.012 0.030 -0.042 -0.020 -0.041 0.009 F-Test 1.679 0.089 1.503 0.142 1.211 0.287 1.530 0.133 0.294 0.982 0.652 0.757 0.310 0.978 1.159 0.322 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

Appendix H: R2, Adjusted R2, F-Test Values, Unstandardized Coefficients, and Significance Values when Variables in the Danger and Authority Categories for Female Genital Slang Terms Are Regressed on Demographic Variables (N = 175)1 Danger (♀) Authority (♀)

Number Percent Avg. Use Avg. Off. Number Percent Avg. Use** Avg. Off. Independent Variables b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. b Sig. Constant 0.264 0.479 0.050 0.606 -1.206 0.032 1.499 0.233 -0.006 0.944 -0.001 0.944 - - -0.006 0.944 Sex (1 = male) 0.051 0.370 0.014 0.338 0.239 0.006 -0.007 0.973 0.017 0.164 0.003 0.164 - - 0.017 0.164 Age -0.015 0.155 -0.001 0.609 -0.011 0.493 -0.044 0.203 -0.001 0.639 0.000 0.639 - - -0.001 0.639 Straight* 0.142 0.255 0.034 0.299 0.163 0.382 0.352 0.400 0.001 0.983 0.000 0.983 - - 0.001 0.983 Black* -0.057 0.560 -0.023 0.366 0.047 0.747 0.161 0.626 0.003 0.891 0.001 0.891 - - 0.003 0.891 Other Race* -0.156 0.162 -0.035 0.221 -0.165 0.321 -0.294 0.430 -0.001 0.954 0.000 0.954 - - -0.001 0.954 Education 0.064 0.306 -0.001 0.935 0.335 0.000 -0.089 0.673 0.002 0.856 0.000 0.856 - - 0.002 0.856 Years In School 0.035 0.138 0.011 0.078 0.044 0.215 0.038 0.628 -0.004 0.458 -0.001 0.458 - - -0.004 0.458 Traditional Student* -0.109 0.365 -0.009 0.776 0.249 0.168 -0.391 0.333 0.003 0.921 0.001 0.921 - - 0.003 0.921 Parent #1‟s -0.029 0.202 -0.008 0.161 -0.020 0.562 -0.024 0.752 0.000 0.971 0.000 0.971 - - 0.000 0.971 Education Parent #1‟s Occupational 0.000 0.917 0.000 0.938 0.001 0.886 0.002 0.837 0.000 0.334 0.000 0.334 - - 0.000 0.334 Prestige R2 0.061 0.048 0.141 0.022 0.026 0.026 - 0.026 Adjusted R2 0.004 -0.01 0.089 -0.037 -0.034 -0.034 - -0.034 F-Test 1.067 0.390 0.833 0.597 2.698 0.004 0.376 0.956 0.434 0.928 0.434 0.928 - - 0.434 0.928 1 Bold indicates significance at p < 0.1 * Dummy variables where 1 equals membership in given status

** Regression Impossible because Average Use = 0 for all 175 cases

Appendix I: Correlations and Significance Values Between Authority Category Variables for Male Genital Slang Terms and Sexism Scale Subscales (N = 175)1 Authority (♂) Number Percent Avg. Use Avg. Off. r Sig. r Sig. r Sig. r Sig. Ambivalent Sexism Inventory Hostile -0.001 0.984 0.009 0.910 0.047 0.541 -0.011 0.889 Anti-Feminism 0.029 0.704 -0.004 0.961 0.043 0.572 0.004 0.960 Heterosexual Intimacy 0.041 0.587 0.043 0.572 0.019 0.801 0.056 0.459 Protective Paternalism 0.016 0.838 -0.007 0.929 0.066 0.383 -0.007 0.925 Comp. Gender Differentiation 0.025 0.746 0.045 0.558 0.081 0.286 0.037 0.623 Modern Sexism Scale

Against „Special Treatment‟ 0.002 0.982 0.007 0.926 0.003 0.971 0.016 0.838 Equality Attained 0.022 0.775 0.030 0.697 0.037 0.626 0.021 0.784 Sexual Beliefs Scale

Token Resistance 0.025 0.746 0.094 0.217 0.021 0.784 0.043 0.575 Leading On Justifies Force 0.090 0.235 0.162 0.032 0.049 0.517 0.109 0.152 Women Like Force 0.043 0.576 0.039 0.605 0.101 0.182 0.029 0.708 Men Should Dominate 0.033 0.668 0.041 0.586 0.128 0.092 0.053 0.483 No Means Stop -0.093 0.221 -0.093 0.220 -0.073 0.340 -0.144 0.058 1 Bold indicates significance at p < 0.1

Appendix J: Correlations and Significance Values Between Abject and Euphemism Category Variables for Male Genital Slang Terms and Sexism Scale Subscales (N = 175)1 Abject (♂) Euphemism (♂) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. Ambivalent Sexism Inventory

Hostile 0.036 0.640 0.050 0.511 0.117 0.125 0.075 0.324 -0.080 0.292 -0.105 0.167 -0.058 0.443 -0.021 0.784 Anti-Feminism -0.026 0.735 0.032 0.675 0.000 0.995 0.071 0.351 -0.013 0.866 -0.052 0.497 0.037 0.628 0.118 0.121 Heterosexual Intimacy 0.045 0.552 0.034 0.651 0.039 0.610 0.034 0.660 -0.078 0.304 -0.037 0.628 -0.039 0.609 0.001 0.990 Protective Paternalism -0.083 0.274 -0.058 0.447 -0.087 0.253 -0.007 0.927 -0.129 0.088 -0.118 0.119 -0.012 0.870 -0.054 0.478 Comp. Gender Differentiation -0.109 0.152 -0.058 0.446 -0.033 0.661 0.003 0.971 -0.028 0.713 0.029 0.706 0.128 0.091 0.021 0.787 Modern Sexism Scale

Against „Special Treatment‟ 0.042 0.585 0.073 0.335 -0.021 0.783 0.125 0.100 -0.017 0.825 -0.051 0.503 -0.045 0.551 0.028 0.708 Equality Attained -0.031 0.682 -0.003 0.972 -0.020 0.794 0.058 0.448 0.005 0.944 0.043 0.576 -0.034 0.655 0.048 0.531 Sexual Beliefs Scale

Token Resistance -0.117 0.123 -0.081 0.287 -0.041 0.586 -0.060 0.431 -0.105 0.167 -0.085 0.266 -0.084 0.271 -0.012 0.872 Leading On Justifies Force -0.047 0.539 -0.015 0.840 0.029 0.705 -0.011 0.888 0.009 0.903 -0.011 0.885 -0.040 0.603 0.065 0.396 Women Like Force -0.071 0.353 -0.044 0.564 -0.018 0.811 0.000 0.999 -0.023 0.767 -0.011 0.884 0.057 0.453 0.086 0.259 Men Should Dominate -0.005 0.943 0.016 0.830 -0.045 0.551 0.012 0.880 -0.063 0.411 -0.022 0.769 0.050 0.512 -0.008 0.915 No Means Stop -0.016 0.830 -0.001 0.990 -0.070 0.355 -0.041 0.587 0.056 0.461 0.017 0.822 0.012 0.877 -0.036 0.633 1 Bold indicates significance at p < 0.1

100

Appendix K: Correlations and Significance Values Between Nonsense and Euphemism+Nonsense Category Vari ables for Male Genital Slang Terms and Sexism Scale Subscales (N = 175)1 Nonsense (♂) Euphemism and Nonsense (♂) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. Ambivalent Sexism Inventory

Hostile -0.030 0.695 -0.052 0.493 -0.058 0.444 0.007 0.924 -0.081 0.285 -0.122 0.107 -0.084 0.267 -0.007 0.928 Anti-Feminism -0.029 0.707 0.002 0.980 -0.072 0.342 0.010 0.891 -0.031 0.684 -0.040 0.604 -0.023 0.767 0.076 0.318 Heterosexual Intimacy -0.049 0.516 -0.042 0.582 0.035 0.649 0.010 0.893 -0.094 0.214 -0.060 0.427 -0.005 0.945 0.008 0.915 Protective Paternalism 0.077 0.311 0.104 0.170 0.090 0.236 -0.022 0.774 -0.037 0.625 -0.016 0.832 0.053 0.484 -0.047 0.534 Comp. Gender Differentiation -0.040 0.599 -0.003 0.969 -0.012 0.873 -0.045 0.550 -0.051 0.506 0.021 0.787 0.088 0.248 -0.021 0.780 Modern Sexism Scale

Against „Special Treatment‟ 0.020 0.798 0.003 0.971 -0.045 0.554 0.067 0.381 0.002 0.976 -0.038 0.614 -0.065 0.389 0.065 0.391 Equality Attained 0.004 0.954 0.033 0.661 0.014 0.854 0.022 0.771 0.007 0.924 0.059 0.441 -0.016 0.835 0.044 0.564 Sexual Beliefs Scale

Token Resistance 0.014 0.851 0.003 0.972 0.118 0.120 0.048 0.528 -0.066 0.384 -0.065 0.392 0.019 0.802 0.028 0.713 Leading On Justifies Force 0.047 0.537 0.030 0.692 0.113 0.138 0.192 0.011 0.042 0.581 0.014 0.857 0.049 0.524 0.178 0.019 Women Like Force -0.008 0.921 -0.035 0.643 0.021 0.787 0.026 0.736 -0.022 0.770 -0.035 0.645 0.057 0.451 0.069 0.367 Men Should Dominate -0.020 0.797 -0.054 0.479 0.004 0.960 -0.011 0.889 -0.061 0.425 -0.058 0.447 0.040 0.597 -0.012 0.870 No Means Stop 0.033 0.665 0.039 0.606 -0.040 0.600 -0.096 0.207 0.066 0.386 0.043 0.574 -0.019 0.804 -0.091 0.230 1 Bold indicates significance at p < 0.1

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Appendix L: Correlations and Significance Values Between Danger and Authority Category Variables for Female Genital Slang Terms and Sexism Scale Subscales (N = 175)1 Danger (♀) Authority (♀) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use* Avg. Off. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. Ambivalent Sexism Inventory

Hostile -0.123 0.106 -0.134 0.077 -0.024 0.753 -0.009 0.910 0.108 0.153 0.108 0.153 - - 0.108 0.153 Anti-Feminism 0.008 0.918 0.014 0.851 -0.010 0.893 0.019 0.802 -0.023 0.764 -0.023 0.764 - - -0.023 0.764 Heterosexual Intimacy -0.147 0.053 -0.155 0.041 -0.072 0.341 -0.064 0.402 0.036 0.635 0.036 0.635 - - 0.036 0.635 Protective Paternalism -0.047 0.538 0.070 0.360 0.080 0.293 -0.063 0.409 -0.010 0.900 -0.010 0.900 - - -0.010 0.900 Comp. Gender Differentiation -0.021 0.780 0.021 0.778 -0.100 0.189 0.080 0.293 0.032 0.671 0.032 0.671 - - 0.032 0.671 Modern Sexism Scale

Against „Special Treatment‟ 0.053 0.489 0.009 0.905 0.098 0.199 -0.013 0.859 0.032 0.678 0.032 0.678 - - 0.032 0.678 Equality Attained -0.059 0.441 -0.044 0.559 0.085 0.263 -0.122 0.107 0.079 0.296 0.079 0.296 - - 0.079 0.296 Sexual Beliefs Scale

Token Resistance -0.124 0.102 -0.044 0.560 -0.072 0.344 -0.127 0.094 -0.030 0.691 -0.030 0.691 - - -0.030 0.691 Leading On Justifies Force -0.045 0.556 -0.078 0.306 -0.101 0.183 -0.029 0.700 -0.037 0.630 -0.037 0.630 - - -0.037 0.630 Women Like Force -0.059 0.440 -0.020 0.790 -0.027 0.719 0.010 0.900 -0.060 0.429 -0.060 0.429 - - -0.060 0.429 Men Should Dominate -0.087 0.252 -0.085 0.264 -0.009 0.906 -0.013 0.866 0.079 0.296 0.079 0.296 - - 0.079 0.296 No Means Stop 0.129 0.089 0.101 0.183 0.066 0.387 0.101 0.185 0.037 0.623 0.037 0.623 - - 0.037 0.623 1 Bold indicates significance at p < 0.1 * Correlations impossible because Average Use = 0 for all 175 cases

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Appendix M: Correlations and Significance Values Between Abject Category Variables for Female Genital Slang Terms and Sexism Scale Subscales (N = 175)1 Abject (♀)

Number Percent Avg. Use Avg. Off.

r Sig. r Sig. r Sig. r Sig.

Ambivalent Sexism Inventory

Hostile 0.147 0.052 0.203 0.007 0.132 0.081 0.106 0.161 Anti-Feminism 0.033 0.665 0.070 0.356 -0.006 0.941 0.028 0.711 Heterosexual Intimacy 0.004 0.956 0.023 0.765 0.017 0.824 0.060 0.427 Protective Paternalism -0.011 0.887 0.003 0.971 0.117 0.124 -0.007 0.931 Comp. Gender Differentiation -0.067 0.376 -0.019 0.798 0.067 0.380 -0.015 0.847 Modern Sexism Scale

Against „Special Treatment‟ 0.100 0.190 0.165 0.029 0.011 0.881 0.061 0.424 Equality Attained -0.009 0.907 0.049 0.521 0.028 0.712 -0.032 0.673 Sexual Beliefs Scale

Token Resistance -0.007 0.928 0.035 0.642 0.057 0.455 -0.018 0.811 Leading On Justifies Force -0.004 0.962 0.026 0.736 -0.069 0.364 0.001 0.989 Women Like Force 0.055 0.473 0.096 0.207 0.074 0.329 0.024 0.756 Men Should Dominate 0.040 0.602 0.099 0.193 0.045 0.550 0.014 0.852 No Means Stop -0.028 0.716 -0.065 0.390 -0.032 0.673 -0.018 0.817 1 Bold indicates significance at p < 0.1

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Appendix N: Correlations and Significance Values Between Nonsense and Euphemism+Nonsense Category Variables for Female Genital Slang Terms and Sexism Scale Subscales (N = 175)1 Nonsense (♀) Euphemism and Nonsense (♀)

Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off.

r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig. r Sig.

Ambivalent Sexism Inventory

Hostile -0.001 0.984 0.009 0.910 0.047 0.541 -0.011 0.889 0.036 0.640 0.050 0.511 0.117 0.125 0.075 0.324 Anti-Feminism 0.029 0.704 -0.004 0.961 0.043 0.572 0.004 0.960 -0.026 0.735 0.032 0.675 0.000 0.995 0.071 0.351 Heterosexual Intimacy 0.041 0.587 0.043 0.572 0.019 0.801 0.056 0.459 0.045 0.552 0.034 0.651 0.039 0.610 0.034 0.660 Protective Paternalism 0.016 0.838 -0.007 0.929 0.066 0.383 -0.007 0.925 -0.083 0.274 -0.058 0.447 -0.087 0.253 -0.007 0.927 Comp. Gender Differentiation 0.025 0.746 0.045 0.558 0.081 0.286 0.037 0.623 -0.109 0.152 -0.058 0.446 -0.033 0.661 0.003 0.971 Modern Sexism Scale

Against „Special Treatment‟ 0.002 0.982 0.007 0.926 0.003 0.971 0.016 0.838 0.042 0.585 0.073 0.335 -0.021 0.783 0.125 0.100 Equality Attained 0.022 0.775 0.030 0.697 0.037 0.626 0.021 0.784 -0.031 0.682 -0.003 0.972 -0.020 0.794 0.058 0.448 Sexual Beliefs Scale

Token Resistance 0.025 0.746 0.094 0.217 0.021 0.784 0.043 0.575 -0.117 0.123 -0.081 0.287 -0.041 0.586 -0.060 0.431 Leading On Justifies Force 0.090 0.235 0.162 0.032 0.049 0.517 0.109 0.152 -0.047 0.539 -0.015 0.840 0.029 0.705 -0.011 0.888 Women Like Force 0.043 0.576 0.039 0.605 0.101 0.182 0.029 0.708 -0.071 0.353 -0.044 0.564 -0.018 0.811 0.000 0.999 Men Should Dominate 0.033 0.668 0.041 0.586 0.128 0.092 0.053 0.483 -0.005 0.943 0.016 0.830 -0.045 0.551 0.012 0.880 No Means Stop -0.093 0.221 -0.093 0.220 -0.073 0.340 -0.144 0.058 -0.016 0.830 -0.001 0.990 -0.070 0.355 -0.041 0.587 1 Bold indicates significance at p < 0.1

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Appendix O: Partial Correlations and Significance Values Between Authority Category Variables for Male Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Authority (♂) Number Percent Avg. Use Avg. Off. ρ Sig. ρ Sig. ρ Sig. ρ Sig. Ambivalent Sexism Inventory Hostile 0.030 0.711 0.001 0.987 -0.002 0.981 0.027 0.732 Anti-Feminism 0.055 0.490 0.064 0.420 0.010 0.899 0.040 0.612 Heterosexual Intimacy 0.059 0.458 0.032 0.684 0.003 0.973 0.071 0.376 Protective Paternalism 0.051 0.524 0.037 0.645 0.043 0.587 0.039 0.624 Comp. Gender 0.068 0.392 0.044 0.584 0.104 0.194 0.080 0.317 Differentiation Modern Sexism Scale

Against „Special -0.011 0.893 -0.012 0.878 -0.042 0.603 -0.001 0.991 Treatment‟ Equality Attained 0.065 0.415 0.048 0.548 0.039 0.627 0.056 0.484 Sexual Beliefs Scale

Token Resistance 0.026 0.743 0.021 0.795 -0.031 0.695 0.023 0.769 Leading On Justifies Force 0.094 0.241 0.086 0.282 0.016 0.840 0.101 0.206 Women Like Force 0.082 0.307 0.057 0.473 0.080 0.314 0.060 0.454 Men Should Dominate 0.041 0.606 0.050 0.534 0.108 0.177 0.055 0.494 No Means Stop -0.068 0.396 -0.103 0.197 -0.060 0.453 -0.115 0.149 1 Bold indicates significance at p < 0.1

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Appendix P: Partial Correlations and Significance Values Between Abject and Euphemism Category Variables for Male Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Abject (♂) Euphemism (♂) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. Ambivalent Sexism Inventory Hostile 0.026 0.747 0.049 0.543 0.124 0.120 0.076 0.340 -0.029 0.719 -0.054 0.500 -0.055 0.488 0.042 0.598 Anti-Feminism -0.014 0.858 0.056 0.484 -0.001 0.987 0.103 0.197 0.025 0.758 -0.010 0.903 0.039 0.623 0.162 0.041 Heterosexual Intimacy 0.115 0.148 0.095 0.233 0.105 0.189 0.079 0.321 -0.084 0.295 -0.040 0.618 -0.070 0.383 0.010 0.899 Protective Paternalism -0.040 0.617 -0.011 0.886 -0.048 0.551 0.045 0.573 -0.120 0.133 -0.099 0.214 -0.019 0.808 0.008 0.923 Comp. Gender -0.054 0.500 -0.014 0.865 0.015 0.854 0.047 0.553 -0.091 0.254 -0.031 0.698 0.087 0.277 0.004 0.956 Differentiation Modern Sexism Scale

Against „Special 0.066 0.408 0.099 0.215 -0.002 0.981 0.176 0.026 0.022 0.781 -0.013 0.869 -0.040 0.618 0.060 0.453 Treatment‟ Equality Attained -0.002 0.982 0.017 0.835 -0.015 0.849 0.083 0.298 0.033 0.681 0.067 0.402 -0.012 0.877 0.048 0.548 Sexual Beliefs Scale

Token Resistance -0.154 0.052 -0.113 0.156 -0.061 0.445 -0.083 0.296 -0.078 0.326 -0.062 0.439 -0.082 0.302 0.021 0.789 Leading On Justifies Force -0.090 0.261 -0.055 0.490 -0.029 0.718 -0.035 0.665 0.042 0.603 0.014 0.863 -0.008 0.919 0.099 0.217 Women Like Force -0.053 0.505 -0.028 0.728 0.007 0.933 0.016 0.842 0.019 0.808 0.027 0.735 0.073 0.362 0.135 0.090 Men Should Dominate -0.022 0.788 0.013 0.872 -0.060 0.453 -0.003 0.968 -0.036 0.651 0.020 0.800 0.052 0.519 0.009 0.911 No Means Stop 0.031 0.696 0.038 0.631 -0.046 0.563 -0.004 0.963 0.050 0.528 0.008 0.923 0.005 0.948 -0.036 0.650 1 Bold indicates significance at p < 0.1

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Appendix Q: Partial Correlations and Significance Values Between Nonsense and Euphemism+Nonsense Category Variables for Male Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Nonsense (♂) Euphemism and Nonsense (♂) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use. Avg. Off. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. Ambivalent Sexism Inventory Hostile -0.059 0.458 -0.052 0.519 -0.116 0.147 -0.003 0.973 -0.063 0.429 -0.079 0.323 -0.118 0.138 0.022 0.780 Anti-Feminism -0.057 0.479 -0.014 0.857 -0.125 0.118 0.002 0.978 -0.023 0.773 -0.018 0.824 -0.054 0.502 0.095 0.234 Heterosexual Intimacy -0.056 0.483 -0.056 0.481 0.044 0.579 0.008 0.925 -0.100 0.210 -0.071 0.374 -0.022 0.778 0.011 0.888 Protective Paternalism 0.062 0.437 0.069 0.389 0.008 0.920 -0.025 0.751 -0.041 0.610 -0.030 0.703 -0.009 0.909 -0.014 0.863 Comp. Gender -0.025 0.754 -0.015 0.849 0.011 0.891 -0.033 0.682 -0.083 0.299 -0.035 0.659 0.072 0.367 -0.021 0.792 Differentiation Modern Sexism Scale Against „Special 0.020 0.802 0.000 1.000 -0.116 0.144 0.098 0.220 0.030 0.704 -0.010 0.896 -0.107 0.179 0.105 0.188 Treatment‟ Equality Attained 0.001 0.989 0.019 0.809 -0.049 0.542 0.038 0.631 0.024 0.762 0.067 0.405 -0.042 0.602 0.055 0.489 Sexual Beliefs Scale Token Resistance -0.001 0.987 -0.021 0.796 0.069 0.387 0.059 0.457 -0.057 0.476 -0.063 0.427 -0.016 0.846 0.055 0.490 Leading On Justifies Force 0.075 0.350 0.059 0.458 0.100 0.212 0.263 0.001 0.083 0.296 0.052 0.512 0.060 0.451 0.246 0.002 Women Like Force -0.027 0.739 -0.071 0.373 -0.036 0.650 0.026 0.742 -0.005 0.947 -0.028 0.723 0.030 0.706 0.097 0.225 Men Should Dominate -0.031 0.700 -0.047 0.554 -0.024 0.763 -0.011 0.886 -0.048 0.549 -0.017 0.831 0.022 0.779 -0.003 0.969 No Means Stop 0.038 0.634 0.024 0.764 -0.041 0.606 -0.116 0.145 0.063 0.428 0.023 0.774 -0.024 0.768 -0.105 0.190 1 Bold indicates significance at p < 0.1

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Appendix R: Partial Correlations and Significance Values Between Authority Category Variables for Female Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Authority (♀)

Number Percent Avg. Use* Avg. Off.

ρ Sig. ρ Sig. ρ Sig. ρ Sig.

Ambivalent Sexism Inventory

Hostile 0.087 0.275 0.087 0.275 - - 0.087 0.275 Anti-Feminism -0.035 0.664 -0.035 0.664 - - -0.035 0.664 Heterosexual Intimacy 0.047 0.553 0.047 0.553 - - 0.047 0.553 Protective Paternalism -0.035 0.657 -0.035 0.657 - - -0.035 0.657 Comp. Gender 0.068 0.392 0.068 0.392 - - 0.068 0.392 Differentiation Modern Sexism Scale

Against „Special -0.004 0.961 -0.004 0.961 - - -0.004 0.961 Treatment‟ Equality Attained 0.057 0.479 0.057 0.479 - - 0.057 0.479 Sexual Beliefs Scale

Token Resistance -0.077 0.336 -0.077 0.336 - - -0.077 0.336 Leading On Justifies Force -0.078 0.326 -0.078 0.326 - - -0.078 0.326 Women Like Force -0.093 0.245 -0.093 0.245 - - -0.093 0.245 Men Should Dominate 0.069 0.389 0.069 0.389 - - 0.069 0.389 No Means Stop 0.047 0.553 0.047 0.553 - - 0.047 0.553 1 Bold indicates significance at p < 0.1 * Partial correlations impossible because Average Use = 0 for all 175 cases

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Appendix S: Partial Correlations and Significance Values Between Euphemism+Nonsense Category Variables for Female Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Euphemism and Nonsense (♀)

Number Percent Avg. Use Avg. Off.

ρ Sig. ρ Sig. ρ Sig. ρ Sig.

Ambivalent Sexism Inventory

Hostile 0.005 0.947 -0.007 0.932 0.106 0.184 0.019 0.817 Anti-Feminism -0.119 0.134 -0.126 0.115 0.050 0.529 -0.023 0.775 Heterosexual Intimacy 0.102 0.200 0.069 0.386 0.173 0.029 0.070 0.377 Protective Paternalism 0.057 0.472 0.069 0.390 0.095 0.235 0.059 0.463 Comp. Gender 0.050 0.528 0.070 0.380 0.138 0.083 0.104 0.193 Differentiation Modern Sexism Scale

Against „Special -0.069 0.385 -0.041 0.604 0.075 0.349 0.035 0.661 Treatment‟ Equality Attained -0.020 0.798 0.030 0.706 0.120 0.133 0.038 0.631 Sexual Beliefs Scale

Token Resistance -0.056 0.487 -0.057 0.477 0.073 0.360 -0.070 0.378 Leading On Justifies 0.086 0.283 0.071 0.372 0.027 0.740 0.086 0.281 Force Women Like Force -0.079 0.325 -0.031 0.694 0.068 0.393 -0.084 0.293 Men Should Dominate -0.098 0.220 -0.039 0.625 -0.063 0.432 -0.131 0.099 No Means Stop 0.020 0.799 0.055 0.494 0.022 0.787 0.010 0.901 1 Bold indicates significance at p < 0.1

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Appendix T: Partial Correlations and Significance Values Between Abject and Euphemism Category Variables for Female Genital Slang Term Variables and Sexism Scale Subscales while Controlling for Demographic Variables (df = 157)1 Abject (♀) Euphemism (♀) Number Percent Avg. Use Avg. Off. Number Percent Avg. Use Avg. Off. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. ρ Sig. Ambivalent Sexism Inventory Hostile 0.147 0.065 0.194 0.014 0.077 0.333 0.110 0.166 -0.078 0.328 -0.068 0.396 0.015 0.849 -0.029 0.718 Anti-Feminism -0.011 0.886 0.019 0.813 -0.034 0.672 0.009 0.908 -0.059 0.459 -0.058 0.465 0.041 0.607 0.046 0.567 Heterosexual Intimacy 0.059 0.461 0.062 0.435 0.012 0.882 0.111 0.162 0.003 0.970 0.011 0.886 0.079 0.319 0.064 0.424 Protective Paternalism 0.003 0.970 0.000 1.000 0.075 0.345 0.001 0.988 -0.163 0.040 -0.117 0.141 -0.036 0.650 -0.015 0.854 Comp. Gender 0.041 0.604 0.093 0.242 0.140 0.078 0.054 0.500 0.000 0.998 0.070 0.382 0.054 0.499 0.030 0.708 Differentiation Modern Sexism Scale Against „Special 0.087 0.274 0.144 0.071 -0.034 0.673 0.048 0.544 -0.102 0.200 -0.119 0.135 0.036 0.651 -0.104 0.191 Treatment‟ Equality Attained -0.016 0.836 0.028 0.725 -0.014 0.858 -0.034 0.671 -0.046 0.563 -0.015 0.850 -0.010 0.904 -0.039 0.622 Sexual Beliefs Scale Token Resistance 0.002 0.975 0.030 0.703 0.011 0.889 -0.015 0.855 -0.087 0.273 -0.068 0.396 0.016 0.845 -0.013 0.870 Leading On Justifies Force -0.030 0.710 -0.003 0.969 -0.113 0.158 -0.016 0.842 0.043 0.589 0.009 0.909 0.026 0.743 0.087 0.273 Women Like Force 0.088 0.270 0.111 0.165 0.032 0.687 0.049 0.540 -0.117 0.140 -0.011 0.886 0.007 0.934 -0.048 0.548 Men Should Dominate 0.000 0.997 0.045 0.576 -0.041 0.604 0.010 0.898 -0.084 0.290 0.030 0.706 -0.001 0.993 -0.100 0.211 No Means Stop 0.002 0.985 -0.039 0.628 -0.002 0.979 0.008 0.922 0.050 0.531 0.034 0.672 -0.007 0.934 0.028 0.723 1 Bold indicates significance at p < 0.1

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