Gender, Race, and Aggression in Mainstream Pornography

Total Page:16

File Type:pdf, Size:1020Kb

Gender, Race, and Aggression in Mainstream Pornography Archives of Sexual Behavior https://doi.org/10.1007/s10508-018-1304-6 ORIGINAL PAPER Gender, Race, and Aggression in Mainstream Pornography Eran Shor1 · Golshan Golriz1 Received: 20 May 2017 / Revised: 3 December 2017 / Accepted: 29 August 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract The role of aggression in pornographic videos has been at the heart of many theoretical debates and empirical studies over the last four decades, with rates of reported aggression ranging widely. However, the interaction between gender and race in the production of aggressive pornographic contents remains understudied and undertheorized. We conducted a study of 172 popular free Internet pornographic videos, exploring gender and racial interactions and the depictions of men and women from various ethnic and racial groups in online pornography. Contrary to our theoretical expectations and to the fndings of previous research, we found that videos featuring Black women were less likely to depict aggression than those featuring White women, while videos featuring Asian and Latina women were more likely to depict aggression. Our fndings call for a reconceptualization of the role of race and ethnicity in pornography. Keywords Pornography · Aggression · Violence · Race · Gender Introduction class shape the experiences of women (in porn and more gener- ally). The few previous attempts to explore these issues empiri- The issue of aggression in pornography has created a divide cally have focused on diferences between two racial groups among feminist scholars. While some have argued that pornog- (most notably Black vs. White) and relied primarily on samples raphy is almost always violent, leading to misogyny and sexual of rental videos, which difer signifcantly in terms of audience, aggression against women (Dines, Jensen, & Russo, 1998; accessibility, length, and production from more recent porno- Dworkin, 1994; Jensen, 2007; Paul, 2005), others suggest that graphic materials. pornography ofers a feld full of contradictory, multilayered, In the current study, we ofer the frst comprehensive theoreti- and complex representations, which are often unharmful and cal discussion and empirical analysis of the interaction between can even be benefcial (Strossen, 1995; Watson & Smith, 2012; gender and major racial and ethnic categories in North America, Willis, 1994). Previous estimates of the prevalence of aggression focusing on White, Black, Asian, and Latino/Latina male and in rental and Internet pornographic videos have varied greatly, female performers. We examine the ways in which the interac- ranging from about 2% to almost 90% of all videos (see our tion between gender and race/ethnicity infuences the content discussion below regarding this diference in reported aggres- of Internet pornographic materials, in particular expressions sion rates). of aggression and afection. Our study is also the frst to ofer Still, one area where theoretical and empirical research various measures of aggression, based on difering defnitions, remains relatively scarce is the study of race and ethnicity, and trying to address ongoing debates in the literature over the “cor- that of the interaction between gender and race in pornographic rect” way to measure aggression in content analyses of sexually materials. Notable feminist race scholars, such as Hill Collins explicit materials (Bridges, Wosnitzer, Scharrer, Sun, & Liber- (2000), have argued that pornography exemplifes the interlock- man, 2010; McKee, 2015). ing relationships between gender and race and that mainstream (White) feminism has often ignored the ways in which race and Literature Review Previous research has looked at aggressive content in porno- * Eran Shor graphic magazines, books, movies, video covers, and Internet [email protected] videos. Estimates of the amount of aggression in these media 1 Department of Sociology, McGill University, 855 vary greatly, ranging from 1.9 (McKee, 2005) to 88.8% (Bridges Sherbrooke Street West, Montreal, QC H3H 2J2, Canada Vol.:(0123456789)1 3 Archives of Sexual Behavior et al., 2010). Previous research, up until 2010, looked almost against White women, while Black men performed more acts exclusively at magazines and books (Barron & Kimmel, 2000; of aggression against White women than against Black women. Dietz & Sears, 1988; Malamuth & Spinner, 1980; Scott & Cuve- Monk-Turner and Purcell (1999) also looked at Black and White lier, 1993; Smith, 1976; Winick, 1985), at online discussion performers in 40 videocassettes, fnding that Black women expe- boards (Harmon & Boeringer, 1997; Mehta & Plaza, 1997; rienced more aggression from both White and Black men than Micheal & Plaza, 1997; Rimm, 1995), or at rented videos (Bar- was the case for White women. The latter experienced the least ron & Kimmel, 2000; Bridges et al., 2010; Brosius, Weaver, amount of aggression when paired with a Black man. Finally, & Staab, 1993; Cowan & Campbell, 1994; Cowan, Lee, Levy, Zhou and Paul (2016) examined 170 Internet videos appearing & Snyder, 1988; Dietz & Sears, 1988; McKee, 2005; Monk- in the “Asian” category. They found that these videos included Turner & Purcell, 1999). These media have substantial difer- a lower mean number of aggressive acts compared with videos ences from free Internet pornography in terms of accessibility, from other categories (e.g., “Blonde,” “teen,” “cumshot,” and afordability, and anonymity, which may afect both the content “big tits”). and the identity of potential users. Only during the last 8 years, While these previous studies serve as important landmarks however, have studies begun to examine more systematically the in our understanding of the role of race and ethnicity in porno- content of free Internet pornographic videos and the prevalence graphic sexual aggression, they share a number of shortcom- of aggression in them (Gorman, Monk-Turner, & Fish, 2010; ings. First, they all defned aggression quite broadly and did not Klaassen & Peter, 2015; Zhou & Paul, 2016). We therefore still consider the issue of consent in their defnition (see more in our know relatively little about the content of these videos (Vannier, “Method” section). Second, they used either a convenience or Currie, & O’Sullivan, 2014). random sample of videos rather than a sample of more highly Furthermore, most previous studies examined women as a watched videos, putting in question the amount of exposure monolithic group of victims, paying little attention to diferences that these videos actually received (and therefore their cultural among women and among men and to the interactions among impact). Furthermore, Cowan and Campbell (1994) and Monk- them. In particular, the role of race and ethnicity in shaping Turner and Purcell (1999) relied on a sample of rented videos, the practices and principles of the adult entertainment indus- which likely difers signifcantly in terms of audience, acces- try remains undertheorized and understudied (Bernardi, 2006; sibility, length, and production from more recent pornographic Brooks & Hebert, 2006; Miller-Young, 2010, 2014; Shimizu, materials available on the web. Finally, all three previous stud- 2007). Hill Collins (2000) argued that we must conceptualize ies focused on one visible minority group (either Black men pornography as an example of the interlocking nature of race, and women or Asian women) and did not make comparisons gender, and class oppression. Dines (2006) noted that although between diferent minority groups and the various gender and racial diferences have traditionally been defned and coded racial interactions among them. through gender, previous feminist analyses of porn have often The current study thus ofers the frst comprehensive theoreti- excluded race, as well as economic and social inequalities. cal discussion and empirical analysis of the interaction between Brooks (2010), who studied the exotic dance industry, also iden- gender and various major racial and ethnic categories. We exam- tifed a void in the theoretical analyses of racial and sexual hier- ine the association between these interactions and various prac- archies within sex industries. Finally, Pyke and Johnson (2003) tices and behaviors in popular Internet pornography, focusing on suggested that this research paucity extends beyond the analysis aggression and degradation on the one hand, and expressions of of sexually explicit materials and sex work, as little empirical afection and pleasure on the other hand. work has integrated the doing of gender with the study of race. Indeed, a review of previous systematic analyses of porno- Theoretical Framework and Research Hypotheses: graphic content shows that most of them have neglected the role Gender, Race/Ethnicity, and Aggression of race and ethnicity, with a few notable exceptions. Smith’s (1976) analysis of paperback “adult-only” books showed that Previous analyses of pornographic materials have often focused non-White ethnicities were almost completely absent. Winick primarily on female performers and the acts done to them. Male (1985) similarly found that only about one percent of porno- performers, their identities, and diferences among them remain graphic magazine content featured non-White women. Brosius invisible in many of these analyses. Following Dines (2006), we et al. (1993), who examined 50 pornographic videotapes, noted argue that a comprehensive gendered approach must take into an increase in the prevalence of African and Asian actors over account both “fuckers”
Recommended publications
  • Explicit Image Detection Using Ycbcr Space Color Model As Skin Detection
    Applications of Mathematics and Computer Engineering Explicit Image Detection using YCbCr Space Color Model as Skin Detection JORGE ALBERTO MARCIAL BASILIO1, GUALBERTO AGUILAR TORRES2, GABRIEL SÁNCHEZ PÉREZ3, L. KARINA TOSCANO MEDINA4, HÉCTOR M. PÉREZ MEANA5 Sección de Estudios de Posgrados e Investigación 1Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Culhuacan Santa Ana #1000 Col. San Francisco Culhuacan, Del. Coyoacán C.P. 04430 MEXICO CITY [email protected], [email protected], [email protected], [email protected], [email protected] Abstract: - In this paper a novel way to detect explicit content images is proposed using the YCbCr space color, moreover the color pixels percentage that are within the image is calculated which are susceptible to be a tone skin. The main goal to use this method is to apply to forensic analysis or pornographic images detection on storage devices such as hard disk, USB memories, etc. The results obtained using the proposed method are compared with Paraben’s Porn Detection Stick software which is one of the most commercial devices used for detecting pornographic images. The proposed algorithm achieved identify up to 88.8% of the explicit content images, and 5% of false positives, the Paraben’s Porn Detection Stick software achieved 89.7% of effectiveness for the same set of images but with a 6.8% of false positives. In both cases were used a set of 1000 images, 550 natural images, and 450 with highly explicit content. Finally the proposed algorithm effectiveness shows that the methodology applied to explicit image detection was successfully proved vs Paraben’s Porn Detection Stick software.
    [Show full text]
  • Is Mainstream Pornography Becoming Increasingly Violent and Do Viewers Prefer Violent Content?
    The Journal of Sex Research ISSN: 0022-4499 (Print) 1559-8519 (Online) Journal homepage: http://www.tandfonline.com/loi/hjsr20 “Harder and Harder”? Is Mainstream Pornography Becoming Increasingly Violent and Do Viewers Prefer Violent Content? Eran Shor & Kimberly Seida To cite this article: Eran Shor & Kimberly Seida (2018): “Harder and Harder”? Is Mainstream Pornography Becoming Increasingly Violent and Do Viewers Prefer Violent Content?, The Journal of Sex Research, DOI: 10.1080/00224499.2018.1451476 To link to this article: https://doi.org/10.1080/00224499.2018.1451476 Published online: 18 Apr 2018. Submit your article to this journal View related articles View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=hjsr20 THE JOURNAL OF SEX RESEARCH,00(00), 1–13, 2018 Copyright © The Society for the Scientific Study of Sexuality ISSN: 0022-4499 print/1559-8519 online DOI: https://doi.org/10.1080/00224499.2018.1451476 “Harder and Harder”? Is Mainstream Pornography Becoming Increasingly Violent and Do Viewers Prefer Violent Content? Eran Shor and Kimberly Seida Department of Sociology, McGill University, Montreal, Quebec, Canada It is a common notion among many scholars and pundits that the pornography industry becomes “harder and harder” with every passing year. Some have suggested that porn viewers, who are mostly men, become desensitized to “soft” pornography, and producers are happy to generate videos that are more hard core, resulting in a growing demand for and supply of violent and degrading acts against women in mainstream pornographic videos. We examined this accepted wisdom by utilizing a sample of 269 popular videos uploaded to PornHub over the past decade.
    [Show full text]
  • Computational RYB Color Model and Its Applications
    IIEEJ Transactions on Image Electronics and Visual Computing Vol.5 No.2 (2017) -- Special Issue on Application-Based Image Processing Technologies -- Computational RYB Color Model and its Applications Junichi SUGITA† (Member), Tokiichiro TAKAHASHI†† (Member) †Tokyo Healthcare University, ††Tokyo Denki University/UEI Research <Summary> The red-yellow-blue (RYB) color model is a subtractive model based on pigment color mixing and is widely used in art education. In the RYB color model, red, yellow, and blue are defined as the primary colors. In this study, we apply this model to computers by formulating a conversion between the red-green-blue (RGB) and RYB color spaces. In addition, we present a class of compositing methods in the RYB color space. Moreover, we prescribe the appropriate uses of these compo- siting methods in different situations. By using RYB color compositing, paint-like compositing can be easily achieved. We also verified the effectiveness of our proposed method by using several experiments and demonstrated its application on the basis of RYB color compositing. Keywords: RYB, RGB, CMY(K), color model, color space, color compositing man perception system and computer displays, most com- 1. Introduction puter applications use the red-green-blue (RGB) color mod- Most people have had the experience of creating an arbi- el3); however, this model is not comprehensible for many trary color by mixing different color pigments on a palette or people who not trained in the RGB color model because of a canvas. The red-yellow-blue (RYB) color model proposed its use of additive color mixing. As shown in Fig.
    [Show full text]
  • Tnemec Colorbook
    COLORBOOK WHITES 00WH Tnemec White � 06WH Albatross � 07WH Winter Mist � 08WH Acropolis � LRV 84% LRV 82% LRV 80% LRV 72% 01WH Ash White � 02WH Iceberg � 03WH Daisy � 04WH Silver Pearl � LRV 84% LRV 84% LRV 75% LRV 76% 12WH Milkweed � 13WH French Vanilla � 14WH Veiled � 15WH Aspen � LRV 78% LRV 73% LRV 78% LRV 72% 15BR Pale � 22BR Nova � 57BR Cloud � 79BR Colliseum � LRV 83% LRV 81% LRV 75% LRV 67% NOTE: Colors represented are digital reproductions of actual standards and will vary in appearance due to differences in monitor and video card output. These digital representations should not be used to finalize color selection(s). Please contact your local Tnemec Coatings Consultant for color-accurate samples or for assistance with suitable primer and finish coat selections and color matching. LRV = Light Reflectance Value � Standard color and gloss warranty is available in this color for Fluoronar and HydroFlon products. Other colors may be included. Contact your Tnemec representative for more information. GRAYS 30GR Comet � 24GR Lightpole � 43GR Constellation � 37GR Gradation � LRV 75% LRV 62% LRV 71% LRV 65% 25GR Grey Day � 31GR Slate Gray � 57GR Aluminum � 38GR Dove Gray � LRV 46% LRV 61% LRV 46% LRV 58% 33GR Gray – ANSI No. 61 � 32GR Light Gray – ANSI No. 70 � 46GR Sinker � 39GR Pigeon � LRV 33% LRV 44% LRV 26% LRV 42% 35GR Black � 34GR Deep Space � 48GR Moon Shadow � 41GR Hammerhead � LRV 4% LRV 12% LRV 10% LRV 17% NOTE: Colors represented are digital reproductions of actual standards and will vary in appearance due to differences in monitor and video card output.
    [Show full text]
  • Kelvin Color Temperature
    KELVIN COLOR TEMPERATURE William Thompson Kelvin was a 19th century physicist and mathematician who invented a temperature scale that had absolute zero as its low endpoint. In physics, absolute zero is a very cold temperature, the coldest possible, at which no heat exists and kinetic energy (movement) ceases. On the Celsius scale absolute zero is -273 degrees, and on the Fahrenheit scale it is -459 degrees. The Kelvin temperature scale is often used for scientific measurements. Kelvins, as the degrees are now called, are derived from the actual temperature of a black body radiator, which means a black material heated to that temperature. An incandescent filament is very dark, and approaches being a black body radiator, so the actual temperature of an incandescent filament is somewhat close to its color temperature in Kelvins. The color temperature of a lamp is very important in the television industry where the camera must be calibrated for white balance. This is often done by focusing the camera on a white card in the available lighting and tweaking it so that the card reads as true white. All other colors will automatically adjust so that they read properly. This is especially important to reproduce “normal” looking skin tones. In theatre applications, where it is only important for colors to read properly to the human eye, the exact color temperature of lamps is not so important. Incandescent lamps tend to have a color temperature around 3200 K, but this is true only if they are operating with full voltage. Remember that dimmers work by varying the voltage pressure supplied to the lamp.
    [Show full text]
  • RGB Color Code According to the Commission for the Geological Map of the World (CGMW), Paris, France
    RGB Color Code according to the Commission for the Geological Map of the World (CGMW), Paris, France Holocene 254/242/236 Tithonian 217/241/247 Famennian 242/237/197 Ediacaran 254/217/106 254/242/224 Upper Neo- Upper Upper 255/242/211 Kimmeridgian 204/236/244 241/225/157 Frasnian 242/237/173 proterozoic Cryogenian 254/204/92 179/227/238 99 254/179/66 Pleistocene "Ionian" 255/242/199 Oxfordian 191/231/241 Middle Givetian 241/225/133 Tonian 254/191/78 255/242/174 241/200/104 Calabrian 255/242/186 Callovian 191/231/229 203/140/55 Eifelian 241/213/118 Stenian 254/217/154 Quaternary 249/249/127 Meso- Gelasian 255/237/179 Bathonian 179/226/227 247/53/ proterozoic Ectasian Middle Emsian 229/208/117 253/204/138 Lower 253/180/98 Pliocene Piacenzian 255/255/191 52/178/201 128/207/216 Bajocian 166/221/224 Pragian 229/196/104 Calymmian 253/192/122 229/172/77 255/255/153 Zanclean 255/255/179 Aalenian 154/217/221 Lochkovian 229/183/90 Statherian 248/117/167 Devonian Pridoli Messinian 255/255/115 Toarcian 153/206/227 230/245/225 Paleo- Orosirian 247/104/152 103/197/202 230/245/225 247/67/112 proterozoic Tortonian 255/255/102 128/197/221 Rhyacian 247/91/137 Jurassic Pliensbachian Ludfordian 217/240/223 Lower Ludlow Proterozoic 247/67/112 255/230/25 Miocene Serravallian 255/255/89 66/174/208 Sinemurian 103/188/216 191/230/207 Gorstian 204/236/221 Siderian 247/79/124 242/249/29 255/255/0 Langhian 255/255/77 78/179/211 Hettangian Wenlock Homerian 204/235/209 Neoarchean 250/167/200 255/255/65 Burdigalian Rhaetian 227/185/219 179/225/182 179/225/194 Sheinwoodian
    [Show full text]
  • Securedge™ and Metal Flat Sheet Color Chart
    EXPERIENCE THE CARLISLE DIFFERENCE SecurEdge™ and Metal Flat Sheet Color Chart STONE WHITE BONE WHITE REGAL WHITE SANDSTONE ALMOND SIERRA TAN BUCKSKIN MEDIUM BRONZE DARK BRONZE ANTIQUE BRONZE MIDNIGHT BRONZE AGED BRONZE MANSARD BROWN BLACK CITYSCAPE SLATE GRAY GRANITE L MUSKET GRAY CHARCOAL IRON ORE HEMLOCK GREEN PATINA GREEN FOREST GREEN HARTFORD GREEN BURGUNDY COLONIAL RED TERRA COTTA CARDINAL RED TEAL MILITARY BLUE PACIFIC BLUE INTERSTATE BLUE AWARD BLUE SILVER P ZINC P WEATHERED ZINC P CHAMPAGNE P COPPER PENNY P AGED COPPER P DREXLUME™ M P = PREMIUM M = MILL FINISH L = LOW GLOSS COLOR = Standard Product P = CRRC Approved Finishes Cool Roof Product Options SR SRI 24 ga x 20" 24 ga x 48" 22 ga x 48" 26 ga x 20" 26 ga x 27.5" 26 ga x 48" 0.032 x 20" 0.032 x 48" 0.040 X 48" 0.050 x 48" 0.063 x 48" Rated Standard Colors Aged Bronze 0.29 29 P Almond 0.53 62 P Antique Bronze 0.29 28 Black 0.20 17 Bone White 0.67 81 P Buckskin 0.38 41 Burgundy 0.24 23 Charcoal 0.27 27 P Cityscape 0.44 49 P Colonial Red 0.32 34 P Dark Bronze 0.26 24 P Forest Green 0.10 6 Hartford Green 0.29 29 Hemlock Green 0.29 29 P Interstate Blue 0.13 8 Iron Ore 0.27 26 Mansard Brown 0.29 29 P Medium Bronze 0.26 26 P Midnight Bronze 0.06 0 Military Blue 0.29 29 P Musket Gray 0.31 32 P Pacific Blue 0.25 24 P Patina Green 0.33 34 P Regal White 0.60 78 Sandstone 0.49 56 P Sierra Tan 0.36 39 P Slate Gray 0.37 40 P Stone White 0.64 77 P Teal 0.26 25 P Terra Cotta 0.36 39 P Low Gloss Colors Aspen Bronze 0.26 26 P Autumn Red 0.32 34 P Chestnut Brown 0.29 29 P Classic Bronze 0.29
    [Show full text]
  • Color Temperature and at 5,600 Degrees Kelvin It Will Begin to Appear Blue
    4,800 degrees it will glow a greenish color Color Temperature and at 5,600 degrees Kelvin it will begin to appear blue. But light itself has no heat; Color temperature is usually used so for photography it is just a measure- to mean white balance, white point or a ment of the hue of a specific type of light means of describing the color of white source. light. This is a very difficult concept to ex- plain, because–”Isn’t white always white?” The human brain is incred- ibly adept at quickly correcting for changes in the color temperature of light; many different kinds of light all seem “white” to us. When moving from a bright daylight environment to a room lit by a candle all that will appear to change, to the naked eye, is the light level. Yet record these two situations shooting color film, digital photographs or with tape in an unbalanced camcorder and the outside images will have a blueish hue and the inside images will have a heavy orange cast. The brain quickly adjust to the changes, mak- ing what is perceived as white ap- pear white, whereas film, digital im- ages and camcorders are balanced for one particular color and anything that deviates from this will produce a color cast. A GUIDE TO COLOR TEMPERATURE The color of light is measured by the Kelvin scale . This is a sci- entific temperature scale used to measure the exact temperature of objects. If you heat a carbon rod to 3,200 degrees, it glows orange.
    [Show full text]
  • 14. Color Mapping
    14. Color Mapping Jacobs University Visualization and Computer Graphics Lab Recall: RGB color model Jacobs University Visualization and Computer Graphics Lab Data Analytics 691 CMY color model • The CMY color model is related to the RGB color model. •Itsbasecolorsare –cyan(C) –magenta(M) –yellow(Y) • They are arranged in a 3D Cartesian coordinate system. • The scheme is subtractive. Jacobs University Visualization and Computer Graphics Lab Data Analytics 692 Subtractive color scheme • CMY color model is subtractive, i.e., adding colors makes the resulting color darker. • Application: color printers. • As it only works perfectly in theory, typically a black cartridge is added in practice (CMYK color model). Jacobs University Visualization and Computer Graphics Lab Data Analytics 693 CMY color cube • All colors c that can be generated are represented by the unit cube in the 3D Cartesian coordinate system. magenta blue red black grey white cyan yellow green Jacobs University Visualization and Computer Graphics Lab Data Analytics 694 CMY color cube Jacobs University Visualization and Computer Graphics Lab Data Analytics 695 CMY color model Jacobs University Visualization and Computer Graphics Lab Data Analytics 696 CMYK color model Jacobs University Visualization and Computer Graphics Lab Data Analytics 697 Conversion • RGB -> CMY: • CMY -> RGB: Jacobs University Visualization and Computer Graphics Lab Data Analytics 698 Conversion • CMY -> CMYK: • CMYK -> CMY: Jacobs University Visualization and Computer Graphics Lab Data Analytics 699 HSV color model • While RGB and CMY color models have their application in hardware implementations, the HSV color model is based on properties of human perception. • Its application is for human interfaces. Jacobs University Visualization and Computer Graphics Lab Data Analytics 700 HSV color model The HSV color model also consists of 3 channels: • H: When perceiving a color, we perceive the dominant wavelength.
    [Show full text]
  • R Color Cheatsheet
    R Color Palettes R color cheatsheet This is for all of you who don’t know anything Finding a good color scheme for presenting data about color theory, and don’t care but want can be challenging. This color cheatsheet will help! some nice colors on your map or figure….NOW! R uses hexadecimal to represent colors TIP: When it comes to selecting a color palette, Hexadecimal is a base-16 number system used to describe DO NOT try to handpick individual colors! You will color. Red, green, and blue are each represented by two characters (#rrggbb). Each character has 16 possible waste a lot of time and the result will probably not symbols: 0,1,2,3,4,5,6,7,8,9,A,B,C,D,E,F: be all that great. R has some good packages for color palettes. Here are some of the options “00” can be interpreted as 0.0 and “FF” as 1.0 Packages: grDevices and i.e., red= #FF0000 , black=#000000, white = #FFFFFF grDevices colorRamps palettes Two additional characters (with the same scale) can be grDevices comes with the base cm.colors added to the end to describe transparency (#rrggbbaa) installation and colorRamps topo.colors terrain.colors R has 657 built in color names Example: must be installed. Each palette’s heat.colors To see a list of names: function has an argument for rainbow colors() peachpuff4 the number of colors and see P. 4 for These colors are displayed on P. 3. transparency (alpha): options R translates various color models to hex, e.g.: heat.colors(4, alpha=1) • RGB (red, green, blue): The default intensity scale in R > #FF0000FF" "#FF8000FF" "#FFFF00FF" "#FFFF80FF“ ranges from 0-1; but another commonly used scale is 0- 255.
    [Show full text]
  • COLOR SELECTION High Gloss Colors Matte Finish Colors Choosing a Color Is a Very Personal Decision, So QUICKIE and ZIPPIE Give You More Options
    POWER CHAIR SHROUD COLORS & COLOR SELECTION High Gloss Colors Matte Finish Colors Choosing a color is a very personal decision, so QUICKIE and ZIPPIE give you more options. From subtle to eye-catching, we offer the Apple Green Copper Silver Matte Black widest spectrum of possibilities. Explore our collection to find the look that suits you! Special Edition White Candy Apple Red High Gloss Black Yellow Digital Camo Available exclusively on QUICKIE 7 R, 7RS and Q7 NextGEN KOLORFUSION ™ Candy Blue Midnight Blue American Flag Woodland Camo Desert Camo Mossy Oak Camouflage Stars and Stripes Candy Purple Pearl Pink Pink Camo Grunge Skulls Zebra* Color match your * Black Zebra Kolorfusion ™ pattern is available on any base color. JAY ® J3 Back to your Shown here on Candy Blue base color. Quickie ® chair! Carbon Fiber Pearl White ©01.2016 Sunrise Medical (US) LLC Available for order MK-100168 Rev. B through JAY Your Way ™ customizations Customer Service: 800.333.4000 www.SunriseMedical.com FRAME COLORS Sparkle Silver, Red Anodized Package Zebra Kolorfusion ™ Glow paint shown in the dark High Gloss Colors Matte Finish Colors Aztec Gold Candy Red Rootbeer Titanium Color Paint Black Electric Blue Sparkle Silver Matte Black Black Cherry Evergreen Sunrise Orange Matte Black Cherry Black Opal Glow Yellow Matte Purple ANODIZED PARTS Blue Opal Green Apple Refer to product order form for anodized part options. Matte Electric Blue Candy Blue Hot Sparkle Pink Black Titanium Grey Gold Blue Matte Evergreen NOTES: Print processes cannot accurately represent paint finishes. Actual colors may vary. Candy Purple Mauve Pink Colors and patterns may vary based on type of chair or frame material.
    [Show full text]
  • The Sex Myth
    ‘As entertaining as it is erudite’ Catherine Hakin, Observer ieielout & ' Praise for The Sex Myth ‘She accomplishes this heroic task with humour, skill and passion in a book that is as entertaining as it is erudite’ Katherine Hakin, Observer ‘An important book . exactly the kind of level-headed analysis that could help to dispel some of the hysteria surrounding the sex industry’ Suzi Godson, The Times ‘There is a lot to admire in The Sex Myth . should be read by anyone claiming an interest in sex and, especially, sex equality’ Katie Law, Evening Standard ‘An enlightening must-read for anyone exposed to the press’ Abby O’Reilly, Independent on Sunday Dr Brooke Magnanti studied Genetic Epidemiology and gained her PhD at the Department of Forensic Pathology, University of Sheffield. Her professional interests include population-based research, stan­ dards of evidence, and human biology and anthropology. In 2009 it was revealed that she is an ex-call girl and author of the bestselling Belle de Jour series of memoirs, which were adapted into the T V series Secret Diary of a Call Girl, starring Billie Piper. Follow Brooke on Twitter @bmagnanti. By Brooke Magnanti Writing as Belle de Jour The Intimate Adventures of a London Call Girl Further Adventures of a London Call Girl Playing the Game Belle de Jour’s Guide to Men Writing as Dr Brooke Magnanti The Sex Myth The Sex Myth Why everything we’re told is wrong Dr Brooke Magnanti First published in Great Britain in 2012 by Weidenfeld & Nicolson This paperback edition published in 2013 by Phoenix, an imprint of Orion Books Ltd, Orion House, 5 Upper St Martin’s Lane London WC2H 9EA An Hachette UK company 1 3 5 7 9 10 8 6 4 2 Copyright © Bizrealm Limited 2012 Bizrealm Limited has asserted Dr Brooke Magnanti’s right to be identified as the author of this work in accordance with the Copyright, Designs and Patents Act 1988.
    [Show full text]