1 Stories About Men: An Analysis of the Intersection of Gender and Screen Presence in Contemporary Top Grossing Films Since 1995 Benjamin Rosenek Introduction Objective The roles of sex and gender in film have been well examined in many capacities. Sociologists, psychologists, and more have studied these two equally important and intertwined ideas for several decades, thanks to the forces of social movements and cultural evolution. Perhaps as a result of these forces, gradual changes in film have occurred over time. The wispy, helpless, and dependent woman of early 20 th century cinema has become decidedly less common and tho ugh the machismo of their male counterparts has proved far more resilient, notions such as male grief and affection are no longer taboo. The face of social reform, however, is one that must be carefully examined. Whether an issue has seen progress or simply alteration is a question that must be addressed through careful research and objective deliberation. As a student of both
2 sociology and psychology, I began my own research into the intersection of sex, gender, and film that, for reasons detailed in the following section, eventually evolved into a question of representation. I grew curious of whether men outnumber women in cinema, much as they do in politics for reasons entirely unrelated to biology or natural ability. I began to questio n the matter of screen presence, and whether or not it has changed with time. Screen presence as a concept is one the majority of film going individuals are at least vaguely familiar with. In any film, a given character may be more or less significant to the plot than other characters and may spend more or less time being seen and heard. In many movies, the matter of which character is the primary protagonist is well advertised by the promotional material. Audiences expect a great deal of Peter Parker in any Spider Man movie, as the character itself is films, such as th e Lord of the Rings trilogy, may have more of an ensemble cast with several equally important characters who are seen and heard for a similar amount of time. Similarly, a ctors and actresses billed in movie previews, posters, and retail packaging help sell films with the promise that they contribute significantly to the product at hand that they will be seen and heard. Performers who are little known or lack a significant following typically have their credentials
3 left for the end credits. For instance the Blu ray release of the name of Johnny Depp (Mad Hatter) on its packaging to the exclusion of every other actor and actress, despite his character being secondary to those of Mia Wasikowska (Alice) and Helena Bonham Ca rter (Red Queen) the latter of whom played significant roles in Sweeney Todd and Fight Club as well and was again upstaged on promotional material by her male colleagues The question is this, then. Do men and women spend roughly equal amounts of time on screen? If there is a difference, has it changed over time? A simple stroll through the film section of your local department store is likely to yield far more male faces than female. Is this representative of the content of those films? The goal of this research therefore, was to examine the relative screen presence of the male and female sexes in top grossing films as a function of time. A sample of films was taken from 1995 through 2010 and submitted to a quantitative content analysis with the purpose of producing ratios representative of how much time men and women in top grossing function of time to determine whether relative screen presence by sex has changed significantly over th e past fifteen years.
4 The results were quite conclusive. Men vastly outweigh women in cinema. Little has changed. Background As mentioned above, the pervasiveness and damaging effects of gender stereotype laden media have been well documented. Studies investigating the content of music videos (Sommers Flanagan, Sommers Flanagan, & Davis, 1993) advertisements on (Browne, 1998) prime time commercials (Ganahl, Prinsen, & Netzley, 2003) magazines (Baker, 2005) and more have found that gender stereotypes are everywhere. The effects of this are consistently negative. Studies have been conduct ed on the effects of exposure to sexist content on children and adults, male and female. These studies have, as a whole, found that people exposed to stereotypes in these media tend to reflect stereotyped views themselves and these views are host to a num ber of social problems For example, s exually explicit material s, such as pornographic videos which are well known t o portray women as sex objects tend to temporarily alter the beliefs of adolescents about women as sex objects (Peter & Valkenburg, 2007) These sex object stereotypes, which often manifest throughout visual media in the form of impossible standards of beauty, have been demonstrated to encourage poor self esteem and promote damaging eating disorders amongst women
5 (Stice, Schupak Neuberg, Shaw, & Stein, 1994) Even positive stereotypes about women (kind, caring, nurturing, etc.) have that are disadvantageous (Jost & Kay, 2003) It is because of research such as this that, upon having made the decision to pursue a research project for the duration of my senior year at the University of Florida, I began with an investigation into the ubiquity of these stereotypes. Choosing top grossing box office hits, which are inarguably viewed by an enormous audience in the United States, I embarked on a project that would eventually lead me beyond the realm of stereotypes in particular and into a much more fu ndamental issue: the amount of time men and women spend on the big screen. Yet before I describe my methods for researching that issue, I would like to offer a brief account of the evolution of my project which I hold to be vital to communicating the importa nce of the topic I fell upon. Naturally, having decided upon content analysis, I first began by seeking existing content analyses on the stereotypes in film. My interest was in both negative and positive stereotypes of gender, ranging from the supposed mechanical incompetence and superior emotional range of women to the single mindedness and heroic qualities of men. What I was able to find perplexed me, however, and while. Despite the ubiquity of films, existing
6 research on gender stereotypes b ears a strange gap Content analysis on popular media has been done, but there h as been little on box office blockbusters undeniably the most widely consumed media in the United States E xisting studies are, instead, much more narrow or specific in their s ampling (As an aside, while there is little doubt that having the financial means to access the myriad of research pay sites available would per articles followed a similar pattern to the free one s I read in depth.) As a firs t example, Neuendorf, Gore and Dalessandro (2010) set out to examine the portrayals of women in James Bond films. They examined 20 separate movies 195 female characters. They active over the years, as well as more likely to be harmed or killed. In fact, their mortality at the end of the film is best attempted to kill James Bond, and their level of sexual activity. Perhaps the first two make good movie sense, as villains tend to bit e the bullet especially those who attempt to take the life of the lead hero or heroine. Yet sexual activity has no business being linked to whether or not these women are being shot to death, blown up, etc. and this trend has been increasing, not decreasin g.
7 Similarly, an examination of 50 English language, North investigated the link between sexual activity and s urvival rate (Welsh, 2010) Results indicated that sexu al ly active female characters were less likely to survive and had significantly longer death scenes as compared to those female characters who did not engage in sexual behaviors. This was consistent over time. Ironically, the research most relevant to my eventual topic struck me at the time as least immediately relevant. An investigation of gender roles in top grossing G rated (Smith, Pieper, Granados, & Choueiti, 2010) films released from 1990 to 2005 revealed that in a sample of 101 films, the females in these films were far more likely to be portrayed young, beautiful, and virtuous. More central to the article, however, was another finding. Male charac ters outnumbered female characters by a ratio of 2.57 to 1. With this and other research in mind, I began my research project. Without going into great detail concerning my methods, dialo gue, etc., obvious or subtle, which invoked a generalization of either sex, positive or negative. Given that I was interested in measuring the frequency with which these stereotypes were evoked, I designed a complex and somewhat
8 convoluted measure for prod ucing quantitative results, with the end goal in mind of determining whether these stereotypes had enjoyed more, less, or roughly the same popularity since 1995. It was less of what I did find that surprised me and more ral attempts to refine my scale, I continuously ran into the same issue: the quantifiable numbers I was producing did not seem to fall in line with my subjective experience with each film. Movies that seemed entirely slanted toward men at the expense of fe male characters were producing scores that were either mild and unremarkable or seemed to bear little correlation with the concerns any given film left me with. Somewhere between the G and the PG 13 action/adventure epic Armageddon I realized that the issue I repeatedly faced was a matter of screen presence over a matter of portrayal. forward example. Its plot follows a downtrodden ant seeking the aid of lar ger, more menacing insects to vanquish the oppressiv e rule of ants by grasshoppers. Naturally, this ant finds a troupe s them as fighters, and unwittingly brought bac k to the ant hill to do battle stereotypes fal ls more in line with jokes about the species of any given insect than with overt sexist humor, and where sex does come into play it still intersects with species the movie
9 ribs an obese caterpillar, a male ladybug, the neurotic eldest daughter of a queen a nt, a wizened and dramatic praying mantis, and so forth. Apart from some particularly chauvinist flies, there was little to note in my research. Yet the problem was important female characters and at least seventeen important males a ratio of 2.83 to 1. Armageddon was more complex. The movie certainly bears its fair share of male stereotypes. The plot centers around a group of gruff, masculine oil rig workers describe the mselves notice to drill a deep hole in a doomsday meteor and stuff it with a nuclear bomb Unsurprisingly, my quantitative notes did seem in touch with the spirit of a film built around the humor found in loud, simple men saving the world in space. Those notes was present: one woman identified with the roughnecks, another was a space ship pilot, and another the estranged wife of a more central character ( and mother to his son ) Yet these three women, along with the wife of a very minor character present only early in the film (with even fewer lines than her husband), complete the list.
10 Returning to Armageddon later, I found that the film had a male to female charac ter ratio of at least 6.33 to 1 and much farther out of proportion if the myriads of minor male background characters throughout the film (military personnel, NASA flight coordinators, etc.) were included. Having completed my measure of screen presence by this point (which I will spent roughly sixteen fold as much time on screen as did the women. Having stumbled across this trend I attempted to find existing research on the matter. Though again my limited means were certainly no help, I was unable to locate any articles pertaining to screen presence aside from the study of g rated films mentioned above, which mentioned cast ratios but not screen time. My curiosity was piqued, and I began my quantitative investigation of male and female screen presence in top grossing films. Method As mentioned above, this research was a secondary (content) analysis of top grossing films. The central goal was to determine whether or not there is a) disparity between men and women in terms of screen presence in top grossing films and b) if so, wh ether there is a trend of change over time. My
11 hypotheses for these questions were first, that male screen presence would outweigh female screen presence and second, that there would be a significant trend across time from 1995 to 2010 in the form of the g ap between male and female screen presence growing narrower a reflection of social change. Sample The ideal sample would have been top grossing films from every year from 1995 through 2010, and at least the top ten. Of course, any sample of film cann ot possibly represent the massive selection of entertainment available for any given year, but by nature top grossing media is consumed by more people than lesser grossing media. Thus, investigating the top grossing films w ill produce results on what the m ost people are watching and provide insight into the trends amongst the most popular and financially successful films if not the majority of films available On the time and budget constraints of a student project, however, analyzing 150 films was f ar from a viable option. After some deliberation, I chose to watch the top seven grossing films of 1995, 1998, 2001, 2004, 2007, and 2010. Choosing the top seven films of these years was somewhat arbitrary, as were the years themselves. That said, I felt that sampling in this manner would provide a comprehensive window on the years studied and that spreading my sampled years evenly across the time frame
12 being studied would provide a reliable conclusion about the content trends of the entire fifteen year pe riod A list of titles sampled follows: For 1995 in order from highest grossing to lowest grossing, the sampled films were: 1) Batman Forever ; 2) Pocahontas ; 3) Ace Ventura: When Nature Calls ; 4) Gol denEye ; 5) Casper 6) Juma nji ; and 7) Se7en For 1998, the sampled films were: 1) Saving Private Ryan ; 2) Armageddon ; 3 ) ; 4) ; 5) The Waterboy ; 6 ) Doctor Dolittle ; and 7) Rush Hour For 2001, the sampled films were: 1) Harry Potter and the ; 2) The Lord of the Ri ngs: Fellowship of the Ring ; 3) Shrek ; 4) Monsters, Inc. ; 5) Rush Hour 2 ; 6) The Mummy Returns ; and 7) Pearl Harbor For 2004, the sampled films were: 1) Shrek 2; 2) Spider Man 2; 3) Meet the Fockers; 4) The Incredibles; 5) Harry Pot ter and the Prisoner of Azkaban; 6) The Day After Tomorrow; and 7) The Bourne Supremacy. For 2007, the sampled films were: 1) Spider Man 3; 2) Shrek 3; 3) Transformers; 4 ) Pirates o f the Caribbean: At 5) Harry Pott er and the Order of the Phoenix; 6) I Am Legend; and 7) The Bourne Ultimatum
13 For 2010, the sampled films were: 1) Toy Story 3; 2) Alic e in Wonderland; 3) Iron Man 2; 4) The Twilight Saga: Eclipse; 5) Harry Potter and the Deathly Hallows Part 1; 6) Inception; and 7) Despicable Me. Design Th e primary goal of this research was to obtain a to sex across the forty two sampled films. Screen presence was defined as the amount of time a film spends focused primarily on film as a whole. Data w ere collected on a character by character basis those considered significan t to the film as a whole (see limitations for more details). The totals for each sex were derived from those data T hese data w ere then used to extrapolate a relationship between the passage of time and the ratio of male to female screen presence. In itially, my intention was to measure the literal screen time of each individual primary character in a given film by pausing the film each time a character appeared, noting the time, and repeating for each shift in scene. However, as my mentor at the Unive rsity of Florida, Dr. Perz, was quick to point out, this would be incredibly impractical for anything more than a detailed analysis of a single movie. The reason for
14 this is the simple matter of time consumption. As a student project, I lacked the help, finances, and time of day required to count the literally seconds each character was shown for every film on my list. It would have taken years. He suggested I instead look into counting sentences of dialogue with tally marks. The first film I attempted this with was Monsters, Inc. However, this immediately presented a problem: some characters talk far more in a given window of time than others, and counting individ ual sentences would produce results vastly weighted in favor of talkative characters. My compromise was to speaking to another, a tally mark was placed beside their name on a sheet of paper. When ano ther character began speaking, they received their mark, and so on. Naturally, this presents problems of its own. Turns alone might also produce skewed results as a character may have very long turns of speech, such as the Presidential speeches of fi lms such as Armageddon. Thus, I created a list of rules as to when to place extra marks. These included the following: 1. If a character sp oke rapidly for over five seconds at a time another mark was placed by their name. Repeat ed every five seconds.
15 2. A chara cter giving a speech or presentation or addressing a crowd, or anything of a similar vein, was awarded another mark for each distinct pause in their speech or presentation such as the end of a statement or pausing for dramatic effect (In practice, th is tend ed to produce somewhat fewer marks than rule #1 The rationale behind this was that characters giving a speech, etc., are typically only physically present on screen for bits and pieces of their speech, while various other scenes or characters are s hown listening or performing other behaviors. ) 3. When two or more characters engage d in heated bickering or excited exchanges that overlap, such as the frequent panicked or angry exchanges between lead characters in Rush Hour, a tally mark was given to each character for every five seconds of the exchange. 4. When a character sings a song, as was the case in several every other line of the song was counted as a turn of speech Given that nearly every song present in the sample was sung in a traditional 4/4 fashion, this resulted in an average of two tally marks per measure. In the case of duets or group pieces where several characters took turns with different lines of song, l ines were counted as
16 ordinary turns of speech. When several characters sang together, each was counted for every other line of song as described above. 5. Characters that did not speak in intelligible language but were nevertheless important to the film were frequently counted on grunts, utterances, or gestures used in place of speech and according to the same rules as speech This was most frequently used for young children. For example, in the films Monsters Inc. and Meet the Fockers, very young children w ith few language skills were pre sent throughout the entirety of each film. Aside from the above issues, another prevalent problem was how to define in quantitative fashion what constituted a s peech for. It was often the case that I took notes on several very minor characters only to exclude them from the totals after completing the film (see limitations for more details ) Although the argument could be made that counting all speech was ideal, s made some the following data more meaningful. After a film had been viewed and counted to completion, dialogue was sorted by sex. All male character dialogue was totaled separately from all female character dialogue. Male dialogue was divided by female dialogue to create a dialogue
17 ratio with numbers above 1 indicating more male than female dialogue and numbers below 1 indicating more female than male dialogue. For example, Batman Forever h ad 528 turns of male dialogue and 89 turn s of female dialogue, for a dialogue ratio of 5.93 (528/89 = 5.93). Separate from dialogue tallies, a simple count of the primary characters of each sex was taken and summed by sex. Male character count was the n divided by female character count to create a cast ratio A total above 1 indicated more male characters than female, and a total below 1 indicated more female characters than male. Batman Forever had 6 primary male characters and 3 female, for a cast ratio of 2 (6/3 = 2). Finally, the dialogue of each sex was divided by the corresponding cast total for that sex, and the resulting male quotient was divided by the corresponding female quotient to create an adjusted dialogue ratio Batman Forever had 528 turn s of male dialogue, divided by 6, to create a quotient of 88. It also had 89 turn s of female dialogue, divided by 3, to create a quotient of 29.6667. Dividing 88 by 29.6667 yields an adjusted dialogue ratio of 2.96. The purpose of the dialog ue ratio is to calculate the actual relative screen presence of one sex to the other. Cast ratio exists both to underline the wide gap between male and female primary characters and to serve as a statistic with which
18 to create the adjusted dialogue ratio The adjusted dialogue ratio serves to measure, on average, the screen presence of the male and female primary characters relative to the number of characters present of that sex In other words, for Batman Forever to achieve an adjusted dialogue ratio of 1 the female primary characters of the film would have needed to spend roughly 2.96 times more time on screen than their actual recorded screen presence indicates that they did; alternatively, the male primary characters would have needed to spend roughly 2.96 times less time on screen to achieve the same results Analysis of Data Once the data w ere collected, I submitted three separate sets of data to Krus k al Wallis (non parametric ANOVA) tests with a p value of 0.05 dialogue ratios, cast ratios and adjusted dialogue ratios The Kruskal Wallis was chosen by my mentor, with the reasoning that my data was not a random sample and did not conform to the assumption of a normal population required by similar tests. These three Kruskal Wallis tests, th erefore, allowed me to cross check the significance of my findings in light of potential disagreements about whether women are less important in film in terms of screen presence or are merely unrepresented
19 For each Kruskal Wallis test, my hypothesis was that the given dependent variable dialogue, cast or adjusted dialogue ratios would vary as a function of time my independent variable. Naturally, my null hypothesis was that the given ratio did not vary as a function of time Were the results of the Kruskal Wallis test to fall below 0.05, I would reject my null hypothesis, and conclude with 95% certainty that dialogue, cast, or adjusted dialogue ratios were a function of time If the results were to fall above 0.05, I would fai l to reject my null hypothesis, and would conclude that the given ratio was not a function of time that there has been no appreciable change in screen presence over the past 15 years. Though analysis was quantitative in nature, subjective insigh t is o ffered after the results. Results Perhaps due to its nature as a film about the war efforts of soldiers drafted into World War 2 all men, historically the film Saving Private Ryan was treated as an outlier for all three tests. As shown in the film by film data avai lable in the appendix on page 24 it had a dialogue ratio 313.33, a cast ratio of 17, and an adjusted dialogue ratio of 18.43. There was one female character at the very end of the film who spoke three turn s. However, for the sake of reference, t he data from Saving
20 Private Ryan are included in the bar grap hs below and in the composite year totals that follow given that alternate tests including this film produced similar results and did not change the outcome in any significant way All three tests resulted in a failure to reject the ir respective null hypothesis. The p values for the dialogue ratio, cast ratio, and adjusted dialogue ratio were 0.2011, 0.6925, and 0.4811, respectively. The raw data for each film by year and ranked gross profits are presented in the aforementioned appendix. Following this are individual bar graphs for the dialogue tallies of each year, as well as for the sum med dialogue tallies of each total year as a whole. Finally, dialogue ratios cast ratios and adjusted dialogue ratios for each total year are presented in the last graph. (For each graph, mouse over any particular bar to see exact data.)
21 0 200 400 600 800 1000 1200 Batman Forever Pocahontas Ace Ventura: When Nature Calls GoldenEye Casper Jumanji Se7en Male vs Female Dialogue 1995 Male Dialogue Female Dialogue 0 200 400 600 800 1000 1200 Saving Private Ryan Armageddon There's Something About Mary A Bug's Life The Waterboy Dr Dolittle Rush Hour Male vs Female Dialogue 1998 Male Dialogue Female Dialogue
22 0 200 400 600 800 1000 1200 Harry Potter and the Sorcerer's Stone Lord of the Rings: Fellowship of the Ring Shrek Monsters Inc Rush Hour 2 The Mummy Returns Pearl Harbor Male vs Female Dialogue 2001 Male Dialogue Female Dialogue 0 200 400 600 800 1000 1200 Shrek 2 Spider-Man 2 Meet the Fockers The Incredibles Harry Potter and the Prisoner of Azkaban The Day After Tomorrow The Bourne Supremacy Male vs Female Dialogue 2004 Male Dialogue Female Dialogue
23 0 200 400 600 800 1000 1200 Spider-Man 3 Shrek 3 Transformers Pirates of the Caribbean: At World's End Harry Potter and the Order of the Phoenix I Am Legend The Bourne Ultimatum Male vs Female Dialogue 2007 Male Dialogue Female Dialogue 0 200 400 600 800 1000 1200 Toy Story 3 Alice in Wonderland Iron Man 2 Twilight: Eclipse Harry Potter and the Deathly Hallows: Part 1 Inception Despicable Me Male vs Female Dialogue 2010 Male Dialogue Female Dialogue
24 0 1000 2000 3000 4000 5000 6000 1995 1998 2001 2004 2007 2010 Male vs Female Dialogue Year Totals Male Dialogue Female Dialogue 0 1 2 3 4 5 6 1995 1998 2001 2004 2007 2010 Ratios Year Totals Dialogue Ratio Cast Ratio Adjusted Dialogue Ratio
25 As can be seen in the above graphs, any improvements in overall ratios are minor and arguable. 2010 has the most equality of any year, while still seeing a dialogue ratio of 2.19 and a cast ratio of 2.15 It does, however, have an adjusted dialogue ratio of 1.02, which is to say that averaged across sex male and female characters had roughly the character per character screen presence. In other words, had the cast ratio of 2010 been closer to 1, assuming the adjust dialogue ratio stayed the same, the dialogue ratio would have followed suit and also grown closer to 1. This is the only year for which this is true; the next closest year is 2004, with an adjusted dialogue ratio of 1.2, while the previous three yea rs each fall between 1.37 and 1.4. On every other front, 2010 is still most comparable to 2004. The cast ratio in 2004 was slightly lower, at 1.94, yet with the aforementioned adjusted dialogue ratio of 1.2 the dialogue ratio is higher at 2.33. Intere stingly, a glance at the year totals above will reveal that all of this manifests not in less male dialogue, but in more female dialogue. This is perhaps due at least in part to the films Alice in Wonderland and Twilight: Eclipse, as each was host to a fem ale protagonist. Alice also had a female antagonist and was the only film on the list to have more total female dialogue than male. The only
26 Pocahontas. Strangely, 2007 is closest to the initial year of the sample, 1995. This is especially true in terms of raw turn counts, with 1995 having 3478 counted male turns and 1067 counted female turns, while 2007 had 3701 and 1071, respectively. 2007 had a lower adjusted dialogue ratio of 1.28 (vs. 1.37) b ut had a markedly higher cast ratio of 2.71 (vs. 2.38) resulting in a higher overall dialogue ratio than 1995 (3.46 vs. 3.26). 1998 has by far the highest ratios of any year. To achieve similar dialogue ratios to 1995, it would have been necessary to exclude not only Saving Private Ryan, but Armageddon as well and Armageddon lacks the war film justification for its incredibly high ratios. That said, the remaining five films of 1998, averaged together, produce a dialogue ratio of 3.39, indicating that it might be more accurate to suggest that 1998 contained the two most male centric films of the sample and that the year as a whole was similar to those surrounding it. The problem with this assertion, however, is that 1995 had films with similar dia logue ratios in the form of Ace Ventura: When Nature Calls and Se7en. The key difference in terms of year total results is that these two films are markedly shorter than their counterparts in 1998, with both Saving Private Ryan
27 and Armageddon coming in at over two and a half hours long. Thus, in order to place the two years on completely equal footing it would become necessary to employ more complicated measures that account for the running time of features. I would argue, however, that this would eschew th e primary purpose of this research, which is to measure the actual media as experienced by the audiences that viewed it. While it is true that there is more screen time in 1998 than 1995, it does not alter the reality that film going audiences in 1998 did spend more time in theatres watching these films and thus were exposed to the ratios of dialogue as currently measured. Indeed, regardless of where one might stand on the above argument, the data for 2001 are closer to 1998 than they are to 1995. In fact, even if one were to exclude the film with the highest dialogue ratio, Lord of the Rings on the basis that it was written during actual war times and has a similar mentality to a film such as Saving Private Ryan, the remaining films still achieve the remarkably high dialogue ratio of 3.91. This is markedly higher than the results of 1995 sans its two highest grossing films and again defeats any kind of trend toward greater equality across t he first three years of this sample. All in all it would appear that this sample fails to yield any results favorable to a growing trend of equality.
28 Discussion Limitations The most basic limitation of this research concerns collection of data by a single observer. This being a small student project, I was the only observer and by extension I have no validity check with which to support my data. For the sake of both time per applied via estimated time, as pausing the film to start and stop a stopwatch would have stretched the viewing of each of the forty two films out for several hours. It is therefore possible that my results are inexact and that the numbers recorded are off by a small amount. That said, my results were so strongly conclusive that the margin of error required to invalidate my findings is tremendous. Several dozens, if not hundreds of turns of speech would have to be omitted from my data in order to change the direction of my findings. The next limitation of note concerns the selection of so subjective means. Initial attempts to develop an exact, significant to the film as a whole all failed, as this requires one to take into account aspects of plot, which are subjective by nature. For instance, a character in The Bourne Ultimatum has
29 but four turns of speech, but he is referenced continually by other characters throughout two thirds of the film. Another character in the same film is an assassin who does not speak until the final ten mi nutes of the film, but he too is shown throughout. As a general rule, characters present in only a single scene of a film or for less than five or so minutes were omitted from results. This leads to what I feel to be the largest limitation of this res earch and the only one to potentially skew my results in a significant way. As my measure of screen presence was based on turns of speech, characters who simply said very little received fewer tally marks, regardless of their visual presence on screen The above mentioned assassin had more screen time than some other characters that had much higher scores of screen presence. This is hardly a hurdle for dialogue ratios or cast ratios but presents a problem for adjusted dialogue ratios A characte r who says little adds their presence to the cast sum of their sex, and by extension increases the number by which dialogue is being divided to create the quotients used for generating the adjusted dialogue ratio This shrinks the quotient for that sex and by extension minimizes their adjusted dialogue ratio In brief, near relative screen presence with this measure, but decrease it.
30 Once again, however, the results are so highly conclusive that I believ e this issue to relatively minor. A more accurate measure would not likely produce vastly different results. Closing thoughts It would seem not much has changed. Though 2010 scores were usually lower across categories than their earlier counterpart s, the next closest year was 2004, not 2007, suggesting random variation and not a consistent trend. In fact, the closest year to 2007 would appear to be 1995 the earliest year recorded in this research Though my early impressions were that there se emed to be some consistency among which genres of film were the biggest offenders, upon completion there seems to be nothing significant in terms of congruency between genre and scores. That said, four films of 2010 had adjusted dialogue ratios weighted i n favor of as closed to an ideal score as possible (scores: Alice in Wonderland 0.42; Iron Man 2 0.74; Twilight: Eclipse 0.93; Harry Potter and the Deathly Hallows: Part 1 0.82). Mind, women were still quite underrepresented, with a cast ratio of 2.15 and a dialogue ratio of 2.19. What the adjusted dialogue ratios of these four films seem to represent is a growing trend of focusing more on the female secondary characters and less on the male.
31 Take for exa mple Iron Man 2, though this is the most extreme example of the four. This film had a cast ratio of 4.5, with nine male primary characters and two female. The dialogue ratio was 3.32, leaving males with more than three times as much total speech as females The adjusted dialogue ratio of 0.74 indicates that those two women, averaged together, had far more turn s than the nine men averaged together. This does not mean, obviously, that they spent a great deal of time on screen. It does mean that there were sev eral male characters that were relatively minor in comparison. In terms of actual turns of speech, my notes indicate that Tony Stark, the main character of Iron Man 2, had 351 turns of speech. His assistant (and later CEO of his company) had 168 turn s fewer than half as many. That said, the next closest character was one of the antagonists, Hammer, at 129, followed characters, the secret agent doubling as secretary Natalie had 57 turns, the primary antagonist Ivan (a strong, silent congressman Stern had 32, the leader of secret organization Nick Howard had 21, and se cret agent Colson had 12. In total, 748 turns of male dialogue and 225 turns of female dialogue were
32 given, with nine characters delivering the former and two delivering the latter. This actually serves to underline my statement about the limitations concerning the deciding of which characters are of excluded minor characters were male, as well as the majority of quie t characters. Most of the latter were strong, stoic men, aforementioned Ivan. Had these characters spoken as much as their more talkative male counterparts, the dialogue ratios for these films would have been even more skewed toward men than accurate data, the inclusion of more characters delivering four or five lines a piece would have inflated the cast ratios and made the ultimately underrepresent ed women in these films seem even more important in comparison with regard to the adjusted dialogue ratio Regardless, the results are quite clear, and give little room for hoping that some kind of cultural change in media is underway. As a closing n ote, I feel it would be enlightening to see a similar method employed to measure the screen presence of characters by race though that too, I expect, has changed very little over the last fifteen years.
33 Works Cited Baker, C. N. (2005, 01 01). Images of Women's Sexuality in Advertisements: A Content Analysis of Black and White Oriented Women's and Men's Magazines. Sex Roles, 52 (1), 13 27. Beasley, B., & Standley, T. (2002). Shirts vs. skins: Clothing as an indicator of gender role stereotyping in video games. Mass Communication and Society, 5 279 293. Browne, B. A. (1998). Gender Stereotypes in Advertising on Children's Television in the 1990s: A Cross National Analysis. Journal of Advertising, 27 (1), 83 96. Burgess, M., Stermer, S., & Burgess S. (2007, 09 01). Sex, Lies, and Video Games: The Portrayal of Male and Female Characters on Video Game Covers. Sex Roles, 57 (5), 419 433. Dill, K. E. (2005). Featuring females : feminist analyses of media; Chapter: Violence, Sex, Race, and Age in Popula r Video Games: A Content Analysis. Washington, D.C.: American Psychological Association. Dill, K. E., & Thill, K. P. (2007). Video Game Characters and the Sexist Media Depictions. Sex Roles, 57 851 864. Dill, K. E., Brown, B. P., & Collins, M. A. (2008). Effects of exposure to sex stereotyped video game characters on tolerance. Journal of Experimental Social Psychology, 44 (5), 1402 1408. Ganahl, D. J., Prinsen, T. J., & Netzley, S. B. (2003, 11 01). A Content Analysis of Prime Time Commercials: A Contextual Framework of Gender Representation. Sex Roles, 49 (9), 545 551. Jost, J. T., & Kay, A. C. (2003, 02). Exposure to Benevolent Sexism and Complementary Gender Stereotypes: Consequences for Specific and Diffuse Forms of System Justification. Stanford GSB Research Paper No. 1789(R) Millers, M. K., & Summers, A. (2007, 11 01). Gender Di fferences in Video Game Characters' Roles, Appearances, and Attire as Portrayed in Video Game Magazines. Sex Roles, 57 (9), 733 742. Neuendorf, K. A., Gore, T. D., & Dalessandro, A. (2010, 06 01). Shaken and Stirre: A Content Analysis of Women's Portrayals in James Bond Films. Sex Roles, 62 (11), 747 761.
34 Peter, J., & Valkenburg, P. M. (2007, 03 01). Adolescents' Exposure to a Sexualized Media Environment and Their Notions of Women as Sex Objects. Sex Roles, 56 (5), 381 395. Sherman, S. R. (1997). Perils of th e Princses: Gender and Genre in Video Games. Western Folklore, 56, No. 3/4 243 258. Smith, S. L., Pieper, K. M., Granados, A., & Choueiti, M. (2010, 06 01). Assessing Gender Related Portrayals in Top Grossing G Rated Films. Sex Roles, 62 (11), 774 786. Som mers Flanagan, R., Sommers Flanagan, J., & Davis, B. (1993, 06 01). What's happening on Music Television? A gender role content analysis. Sex roles, 28 (11), 745 753. Stice, E., Schupak Neuberg, E., Shaw, H. E., & Stein, R. I. (1994, 11). Relation of Media Exposure to Eating Disorder Symptomatology: An Examination of Mediating Mechanisms. Journal of Abnormal Psychology, 103 (4), 836 840. Welsh, A. (2010, 06 01). On the Perils of Living Dangerously in the Slasher Horror Film: Gender Differences in the Associat ion Between Sexual Activity and Survival. Sex Roles, 62 (11), 762 773.
35 Appendix Film by Film Data 1995 Rating Run Time (minutes) Male Dialogue Female Dialogue Male Cast Female Cast Dialogue Ratio Cast Ratio Adjusted Dialogue Ratio 1. Batman Forever PG 13 121 528 89 6 3 5.93 2 2.96 2. Pocahontas G 91 408 256 9 3 1.59 3 0.53 3. Ace Ventura: When Nature Calls PG 13 94 441 10 8 1 44.1 8 5.51 4. GoldenEye PG 13 130 485 165 9 5 2.92 2.25 1.63 5. Casper G 101 428 232 8 4 1.84 2 0.92 6. Jumanji PG 103 376 268 5 4 1.4 1.25 1.12 7. Se7en R 127 812 47 5 1 17.28 5 3.46 1995 totals 767 3478 1067 50 21 3.26 2.38 1.37 1998 Rating Run Time (minutes) Male Dialogue Female Dialogue Male Cast Female Cast Dialogue Ratio Cast Ratio Adjusted Dialogue Ratio 1. Saving Private Ryan R 169 940 3 17 1 313.33 17 18.43 2. Armageddon PG 13 155 1297 83 19 3 15.63 6.33 2.47 3. There's Something About Mary R 119 845 387 12 7 2.18 1.71 1.27 4. A Bug's Life G 96 663 276 17 6 2.4 2.83 0.85 5. The Waterboy PG 13 89 452 118 17 2 3.83 8.5 0.45 6. Dr Dolittle PG 85 812 166 14 7 4.89 2 2.45 7. Rush Hour PG 13 97 616 52 9 2 11.8 4.5 2.63 1998 totals 810 5625 1085 105 28 5.18 3.75 1.38
36 2001 Rating Run Time (minutes) Male Dialogue Female Dialogue Male Cast Female Cast Dialogue Ratio Cast Ratio Adjusted Dialogue Ratio 1. HP: Sorcerer's Stone PG 152 518 133 12 4 3.9 3 1.3 2. LotR : Fellowship of the Ring PG 13 178 755 76 14 2 9.93 7 1.42 3. Shrek PG 90 403 152 3 2 2.65 1.5 1.77 4. Monsters Inc PG 93 518 119 6 3 4.35 2 2.18 5. Rush Hour 2 PG 13 91 650 64 6 2 10.2 3 3.39 6. Mummy Returns PG 13 130 488 120 9 2 4.1 4.5 0.9 7. Pearl Harbor PG 13 183 690 248 13 5 2.2 2.6 1.07 2001 totals 917 4022 912 63 20 4.41 3.15 1.4 2004 Rating Run Time (minutes) Male Dialogue Female Dialogue Male Cast Female Cast Dialogue Ratio Cast Ratio Adjusted Dialogue Ratio 1. Shrek 2 PG 93 528 213 5 3 2.48 1.6 1.49 2. Spider Man 2 PG 13 127 387 125 5 2 3.1 2.5 1.24 3. Meet the Fockers PG 13 108 751 388 5 4 1.94 1.25 1.55 4. The Incredibles PG 115 430 327 7 4 1.3 2.75 0.75 5. HP: Prisoner of Azkaban PG 142 608 168 14 4 3.62 3.5 1.03 6. Day After Tomorrow PG 13 123 545 138 17 7 3.95 2.43 1.63 7. Bourne Supremacy PG 13 108 267 150 9 8 1.78 1.8 1.58 2004 totals 816 3516 1509 62 32 2.33 1.94 1.2
37 2007 Rating Run Time (minutes) Male Dialogue Female Dialogue Male Cast Female Cast Dialogue Ratio Cast Ratio Adjusted Dialogue Ratio 1. Spider Man 3 PG 13 139 516 204 9 5 2.53 2.25 1.41 2. Shrek 3 PG 92 553 105 9 4 5.27 2.25 2.34 3. Transformers PG 13 144 862 165 21 3 5.22 7 0.75 4. Pirates: At World's End PG 13 169 748 150 14 2 4.99 7 0.71 5. HP: Order of the Phoenix PG 13 138 452 204 14 6 2.22 2.33 0.95 6. I Am Legend PG 13 100 199 148 1 6 1.34 0.167 8.07 7. Bourne Ultimatum PG 13 116 371 95 8 2 3.9 4 0.98 2007 totals 898 3701 1071 76 28 3.46 2.71 1.28 2010 Rating Run Time (minutes) Male Dialogue Female Dialogue Male Cast Female Cast Dialogue Ratio Cast Ratio Adjusted Dialogue Ratio 1. Toy Story 3 G 102 716 250 20 10 2.86 2 1.43 2. Alice in Wonderland PG 108 286 306 9 4 0.93 2.25 0.42 3. Iron Man 2 PG 13 124 748 225 9 2 3.32 4.5 0.74 4. Twilight: Eclipse PG 13 124 476 375 15 11 1.27 1.36 0.93 5. HP: Deathly Hallows p1 PG 13 146 482 196 18 6 2.46 3 0.82 6. Inception PG 13 148 826 206 11 3 4.01 3.67 1.09 7. Despicable Me PG 95 332 207 4 4 1.6 1 1.6 2010 totals 847 3866 1765 86 40 2.19 2.15 1.02
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