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Inequality in 700 Popular Films: Examining Portrayals of Gender, Race, & LGBT Status from 2007 to 2014

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Abstract and Figures

Each year, USC Annenberg’s Media, Diversity, & Social Change Initiative produces a report examining gender and race/ethnicity on screen and behind the camera across the 100 top‐grossing fictional films. A total of 700 films and 30,835 characters have been analyzed across the 100 top‐grossing films of 2007, 2008, 2009, 2010, 2012, 2013, and 2014 (excluding 2011). All speaking or named characters were assessed for demographics, domestic traits, and hypersexualization. For the 100 top movies of 2014, we also examined qualitatively whether characters were portrayed as Lesbian, Gay, Bisexual, and/or Transgender (LGBT). Turning to behind the camera, the gender of directors, writers, and producers of the 100 top films of 2014 was assessed. We also examined female and Black directors working across the 700 top films. This year, the prevalence of Asian directors was noted across the most popular movies as well. To date, this is clearly the most comprehensive longitudinal research report on gender and race/ethnicity across 700 top‐grossing films. Only differences of 5% or greater are noted to avoid making noise about trivial deviations (1‐2%).
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Inequality in 700 Popular Films:
Examining Portrayals of Gender, Race,
& LGBT Status from 2007 to 2014
Dr. Stacy L. Smith | Marc Chouei | Dr. Katherine Pieper
Media, Diversity, &
Social Change Initiative
slsmith@usc.edu
Traci Gillig | Dr. Carmen Lee | Dylan DeLuca
&
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
Inequalityin700PopularFilms:
ExaminingPortrayalsofCharacterGender,Race,&LGBTStatusfrom2007to2014
Dr.StacyL.Smith,MarcChoueiti,Dr.KatherinePieper
&
TraciGillig,Dr.CarmenLee,DylanDeLuca
Media,Diversity,&SocialChangeInitiative
slsmith@usc.edu
Eachyear,USCAnnenberg’sMedia,Diversity,&SocialChangeInitiativeproducesareportexamininggenderand
race/ethnicityonscreenandbehindthecameraacrossthe100topgrossingfictionalfilms.Atotalof700films
and30,835charactershavebeenanalyzedacrossthe100topgrossingfilmsof2007,2008,2009,2010,2012,
2013,and2014(excluding2011).Allspeakingornamedcharacterswereassessedfordemographics,domestic
traits,andhypersexualization.Forthe100topmoviesof2014,wealsoexaminedqualitativelywhether
characterswereportrayedasLesbian,Gay,Bisexual,and/orTransgender(LGBT).
Turningtobehindthecamera,thegenderofdirectors,writers,andproducersofthe100topfilmsof2014was
assessed.WealsoexaminedfemaleandBlackdirectorsworkingacrossthe700topfilms.Thisyear,the
prevalenceofAsiandirectorswasnotedacrossthemostpopularmoviesaswell.Todate,thisisclearlythemost
comprehensivelongitudinalresearchreportongenderandrace/ethnicityacross700topgrossingfilms.Only
differencesof5%orgreaterarenotedtoavoidmakingnoiseabouttrivialdeviations(12%).
KeyFindings
Gender.Only30.2%ofthe30,835speakingcharactersevaluatedwerefemaleacrossthe700topgrossingfilms
from2007to2014.Thiscalculatestoagenderratioof2.3to1.Only11%of700filmshadgenderbalancedcasts
orfeaturedgirls/womeninroughlyhalf(4554.9%)ofthespeakingroles.
Atotalof21ofthe100topfilmsof2014featuredafemaleleadorroughlyequalcolead.Thisissimilartothe
percentagein2007(20%),buta7%decreasefromthe2013sample(28%).
In2014,nofemaleactorsover45yearsofageperformedaleadorcoleadrole.Onlythreeofthefemaleactors
inleadorcoleadroleswerefromunderrepresentedracial/ethnicbackgrounds.Nofemaleleadsorcoleads
wereLesbianorBisexualcharacters.
Lessthanaquarterofallspeakingcharacterswerefemaleinthetopanimatedfilmsof2014,whichisa7.4%
decreasefrom2010butnochangefrom2007.Only21.8%ofspeakingcharactersinaction/adventurefilmswere
female,whichdidnotdifferfrom2010or2007.34%ofcharactersin2014comedieswerefemale.
Across700films,atotalof9,522characterswerecoded40‐to64yearsofage.Lessthanaquarter(21.8%)of
thesecharacterswerewomen.Only19.9%ofthemiddleagedcharacterswerefemaleacrossthe100topfilms
of2014.Thisisnotdifferentfromthepercentagein2007.
In2014,femalesofallagesweremorelikelythanmalestobeshowninsexyattire(27.9%offemalesvs.8%of
males),withsomenudity(26.4%offemalesvs.9.1%ofmales)andreferencedasphysicallyattractive(12.6%of
femalesvs.3.1%ofmales).
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
2
Examiningpatternsofsexualizationbyagein2014revealedthatfemaleteens(1320yearolds)werejustas
likelytobesexualizedasyoungadultfemales(2139yearolds).Middleagedfemales(4064yearolds)wereless
likelythanthesetwogroupstobesexualized.
Acrossthe100topfilmsof2014,only15.8%ofcontentcreatorsworkingasdirectors,writers,andproducers
werewomen.Womenonlyaccountedfor1.9%ofdirectors,11.2%ofwriters,and18.9%ofproducers.Put
differently,only2womendirectedacrossthe100topfilmsof2014.Thisisnotdifferentfrom2013(2female
directorsacross100topfilms)or2007(3femaledirectorsacross100topfilms).Twentyeightwomenhave
workedasdirectorsacrossthe700topfilmsfrom2007to2014.OnlythreewereAfricanAmerican.
Intheaggregate,filmswithatleastonefemalescreenwriterattachedhavemorefemalecharactersandmore
women40‐to64‐yearsofageonscreenthanfilmswithoutafemalescreenwriterattached.Also,filmswitha
femaleleadorcoleadwereassociatedwithmoregirls/womenonscreenthanthosewithoutafemaleleadorco
leadattached.
Race/Ethnicity.Ofthosecharacterscodedforrace/ethnicityacross100topfilmsof2014,73.1%wereWhite,
4.9%wereHispanic/Latino,12.5%wereBlack,5.3%wereAsian,2.9%wereMiddleEastern,<1%wereAmerican
Indian/AlaskanNativeorNativeHawaiian/PacificIslander,and1.2%werefrom“other”racialand/orethnic
groupings.Thisrepresentsnochangeintheportrayalofapparentrace/ethnicityfrom20072014.
Only17ofthe100topfilmsof2014featuredaleadorcoleadactorfromanunderrepresentedracialand/or
ethnicgroup.Anadditional3filmsdepictedanensemblecastwith50%ormoreofthegroupcomprisedof
actorsfromunderrepresentedracial/ethnicbackgrounds.
Justoveraquarterofcharactersinactionand/oradventure(26.1%)andcomedyfilms(26.5%)arefrom
underrepresentedracial/ethnicgroupsacrossthe100topfilmsof2014.Thisrepresentsnochangefrom2007or
2010.
Incomparisontotopanimatedfilmsof2007,a25.4%increaseinthepercentageofunderrepresented
characterswasobservedinthetopanimatedfilmsof2014.However,overhalfofthese2014characters
appearedinoneanimatedfilm,TheBookofLife.Evenwithoutthismovie,thereisstillasignificantincreasein
thepercentageofunderrepresentedspeakingcharactersinanimatedfilmsfrom2007to2014.
In2014,17filmsdidnotfeatureoneBlackorAfricanAmericanspeakingcharacter.Thisisthesamenumberof
movieswithoutBlackcharactersacrossthe100topfilmsof2013.Over40moviesacrossthe2014sampledid
notdepictanAsianspeakingcharacter.
Acrossthe100topfilmsof2014,only5ofthe107directors(4.7%)wereBlack.OneBlackdirectorhelmedtwo
picturesandonlyonewasfemale.Only45Blackdirectorshavebeenattachedtothe700topgrossingfilms.This
represents5.8%ofallhelmersintheyearsanalyzed.
Only19Asiandirectorsworkedacrossthe700topgrossingfilms.Thisisanoverallpercentageof2.4%.Only1
Asiandirectorwasfemaleacrossthefilmsanalyzedandwaslistedasacodirector.
LGBT.Across4,610speakingcharactersinthe100topfilmsof2014,only19wereLesbian,GayorBisexual.Not
oneTransgendercharacterwasportrayed.TencharacterswerecodedasGay,4wereLesbian,and5were
Bisexual.Only14moviessamplewidefeaturedanLGBdepictionandnoneofthosefilmswereanimated.
OftheLGBcharacterscoded,nearlytwothirdsweremale(63.2%)andonly36.8%werefemale.LGBcharacters
werealsopredominantlyWhite(84.2%).Only15.8%werefromunderrepresentedracial/ethnicbackgrounds.
Prevalance of female speaking characters across 700 films
Of the 100 top films in 2014...
Ratio of males
to females
Tot al n umb er of
speaking
characters
INEQUALITY IN 700 POPULAR FILMS
MEDIA, DIVERSITY, & SOCIAL CHANGE INITIATIVE
USC ANNENBERG
21
FEMALES ARE NOTICEABLY ABSENT IN FILM
FEMALES RARELY DRIVE THE ACTION IN FILM
07 08 09 10 12 13 14
© 2015 DR. STACY L. SMITH | GRAPHICS: PATRICIA LAPADULA
@MDSCInitiative slsmith@usc.edu
2.3 : 1
30,835
Percentage of
700 films with
Balanced Casts
11%
FEATURED A
FEMALE LEAD
OR CO LEAD
AND OF THOSE LEADS AND CO LEADS*...
3
0
FEMALE ACTORS WERE FROM
UNDERREPRESENTED RACIAL /
ETHNIC GROUPS
FEMALE ACTORS WERE AT
LEAST 45 YEARS OF AGE OR
OLDER
29.9 30.3 28.1
29.2
28.4
32.8 32.8
FEMALES ARE AN ENDANGERED SPECIES IN ACTION, ANIMATION, & MIDDLE AGE
07 10 14 07 10 14 07 10 14
ACTION AND/OR
ADVENTURE
ANIMATION MIDDLE AGE
40-64 YEAR OLDS
20% 20.9%
30.7%
21.1% 21.1% 19.9%
23.3%
23.3% 21.8%
*Excludes films w/ensemble casts
% of female speaking characters % of female speaking characters % of female speaking characters
17
26.9%
THE MALE GAZE: FEMALES FUNCTION AS EYE CANDY IN 100 TOP FILMS OF 2014
DISTORTED DEMOGRAPHY? RACE/ETHNICITY IN 100 TOP FILMS OF 2014
A CONCEALED COMMUNITY: LGBT CHARACTERS IN 100 TOP FILMS OF 2014
WHITE UNDERREPRESENTED
SEXY ATTIRE SOME NUDITY ATTRACTIVE
MALES
FEMALES
HISPANIC
BLACK
ASIAN
OTHER
17
FILMS HAVE NO BLACK OR AFRICAN
AMERICAN SPEAKING CHARACTERS
FILMS HAD A LEAD/CO LEAD PLAYED
BY AN ACTOR FROM AN UNDER-
REPRESENTED RACE / ETHNICITY
FILMS HAVE NO ASIAN
SPEAKING CHARACTERS
40+
4
5
LESBIAN
BISEXUAL
GAY
SPEAKING CHARACTERS ONLY... 0TRANSGENDER
10
4,610
© 2015 DR. STACY L. SMITH | GRAPHICS: PATRICIA LAPADULA
8%
27.9%
9.1%
26.4%
3.1%
12.6%
OF THE 100 TOP FILMS OF 2014...
% of underrepresented characters:
*These percentages have not changed since 2007
WHITE
HAD NO LGB
CHARACTERS
73.1%
86
14
84.2%
15.8%
4.9%
12.5%
5.3%
4.2%
HAD 1 OR MORE
LGB CHARACTERS
13-20 yr old
females are just as
likely as 21-39 yr olds
females to be shown
in sexy attire & with
some nudity.
OF THE 19 LGB CHARACTERS...
OF
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
Inequalityin700PopularFilms:
ExaminingCharacters’Gender,Race,&LGBTStatusfrom2007to2014
Dr.StacyL.Smith,MarcChoueiti,Dr.KatherinePieper
&
TraciGillig,Dr.CarmenLee,DylanDeLuca
Media,Diversity,&SocialChangeInitiative
UniversityofSouthernCalifornia
AnnenbergSchoolforCommunication&Journalism
3502WattWay,Suite222223
LosAngeles,CA90089
slsmith@usc.edu
Eachyear,USCAnnenberg’sMedia,Diversity,&SocialChangeInitiativeproducesareport
examininggenderandrace/ethnicityonscreenandbehindthecameraacrossthe100top
grossingfictionalfilms.Themostpopularnarrativemoviesarederivedfromdomesticearnings
asreportedbyBoxOfficeMojo.1Atotalof700filmshavebeenanalyzed,the100topgrossing
filmsof2007,2008,2009,2010,2012,2013,and2014(excluding2011).
Allspeakingornamedcharacters2areassessedfordemographics(age,gender,race/ethnicity),
domestictraits(parentalstatus,relationalstanding),andappearanceindicators(sexyattire,
nudity,physicalattractiveness).3Forthe100topgrossingfilmsof2014,wealsoexamined
qualitativelywhethercharactersareportrayedasLesbian,Gay,Bisexual,and/orTransgender
(LGBT)aswellasaseriesofcontextualvariablessurroundingthesedepictions.Thissupplements
GLAAD’sfindingsonfilmfromthepastfewyears.
Turningtobehindthecamera,thegenderofdirectors,writers,andproducersofthe100top
filmsof2014wereculledfromindustrydatabasesandonlinesources.Wealsotakeacloselook
atfemaleandBlackdirectorsworkingacrossthe700topfilms,whichshouldcomplementother
research(e.g.,ColumbiaUniversity,UCLA’sBuncheCenter)examiningHispanicsand
underrepresentedracial/ethnicgroupsworkingbehindthecamerainfilmandtelevision.This
year,wealsoexaminethenumberofAsiandirectorsacrossthe700topfilms.

Todate,thisisthemostcomprehensivelongitudinalresearchreportongenderand
race/ethnicityacross100topgrossingfilms.Thestudymethodologycanbefoundinthe
footnotessection.Below,wedividethereportintothreemajorsectionscorrespondingtopublic
concernonissuesofrepresentation:1)gender,2)race/ethnicity,and3)LGBTstatus.Within
eachsection,thefindingsfor2014willbepresentedfirstfollowedbyananalysisofchangeover
timeonselectedvariables.Onlysignificant(p<.05)differencesof5%ormorewillbenotedto
avoidreportingonmeaninglessdeviations(12%).Though,notallanalysesweresubjectedto
statisticaltestsandtypically,butnotalways,5%differencesfocuson2007vs.2014orthetwo
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
7
mostrecentyearsexamined(2013vs.2014).Theuseofnreferstothesamplesizeof
characters,films,orcontentcreatorsperanalysis.
GenderOnScreen&BehindtheCamerainFilm
OnScreenPrevalence
Acrossthe100topfilmsof2014,atotalof4,610speakingornamedcharacterswereevaluated.4
Ofthesecharacters,28.1%(n=1,297)werefemaleand71.9%(n=3,313)weremale.Thegender
ratiois2.6onscreenmalecharacterstoevery1onscreenfemalecharacter.Asilluminatedin
Table1,thepercentageoffemalecharactersfrom2007to2014hasnotmeaningfullychanged.
Matteroffact,the2014percentageis1.8%lowerthanthatobservedin2007and.6%lower
thanthepercentage(28.7%)weobservedinasetofpopularfilmsfrom1990to1995.5Inasmall
sampleofmoviesreleasedfrom1946to1955,otherresearchhasdemonstratedthatonly25%
ofonscreencharacterswerewomen.6Despitetheactivismandattentiondevotedtoraising
awarenessonthistopicinthepopularpress,theprevalenceofgirlsandwomenonscreenhasnot
changedinover50years.
Table1
PrevalenceofFemaleCharactersOnScreen:2007to2014
Measures2007200820092010201220132014Total
%ofFemaleChars29.9%32.8%32.8%30.3%28.4%29.2%28.1%30.2%
%ofBalancedCasts12%15%17%4%6%16%9%11%
RatioofMstoFs2.35to12.05to12.05to12.3to12.51to12.43to12.6to12.3to1
Total#ofChars4,3794,3704,3424,1534,4754,5064,61030,835
Total#ofFilms100100100100100100100700
Note:OnlyfictionalfilmsbasedondomesticU.S.grossasreportedbyBoxOfficeMojowerecodedandanalyzed.
Documentarieswerenotevaluatedasapartofthetop100.2011isnotincludedinthesample.
Focusingonleads,atotalof21filmsfeaturedafemaleleadorroughlyequalcoleadacrossthe
sampleof100filmsin2014.Thisissimilartothepercentagein2007(20%),buta7%decrease
fromthe2013sample(28%).Threefemaleactorsthatplayleads/coleadsarefrom
underrepresentedracial/ethnicbackgrounds.Noleadsorcoleadsareplayedbyfemaleactors
over45yearsofage.
Acrossthe2014movies,storieswithafemalelead/coleadfeaturedsignificantlymorefemale
charactersonscreen(41.2%)thanthosestorieswithoutafemalelead(25.5%).7Afull47
narratorswereidentifiedacrossthe100mostpopularmoviesof2014.Only21.3%werefemale
and78.7%weremale.Thisisaratioof3.7malenarratorstoeveryonefemalenarrator.
Thepercentageoffilmswithagenderbalancedcastwasalsoevaluated.Agenderbalancedcast
isonethatfeaturesgirlsandwomeninroughlyhalf(4554.9%)ofthespeakingpartsonscreen.
Only9%ofthe2014filmsweregenderbalanced,whichisa7%decreasefromlastyearbutno
changefrom2007.Only5ofthe100topfilmsof2014hadmorefemales(>55%)thanmaleson
screenwhile15moviescastgirlsandwomenin15%orfewerspeakingroles.
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
8
Thepercentageoffemalecharactersonscreendifferedtrivially(<5%)acrossthreeratings
(PG=28%,PG13=26.4%,R=30.5%).OnlyonemoviewasratedGacrossthesampleof100top
filmsin2014.Assuch,thepercentageoffemalesisnotreportedforgeneralaudiencefilms.8
Turningtogenre,wewereinterestedinthreespecificstorycategories:animation,actionand/or
adventure,andcomedy.AsdepictedinTable2,lessthanaquarterofallspeakingcharacters
werefemaleinanimationin2014whichisa7.4%decreasefrom2010butnochangefrom2007.
Actionand/oradventureaswellascomedydidnotdiffermeaningfullyfrompreviousyears.
Thesefindingssuggestthatactionandanimationprobablylowertheoverallpercentageoffemales
onscreen.Consequently,thesearethegenresthatactivistsneedtotargetforchange.
Table2
PrevalenceofFemaleCharactersOnScreenbyFilmGenre:2007,2010,2014
Actionor
AdventureAnimationComedy
200720102014200720102014200720102014
%offemalesonscreen
20%23.3%21.8%20.9%30.7%23.3%36%36%34%
Note:OnlythepercentageoffemalecharactersisreportedinTable2.Forthepercentageofmalespeaking
characters,subtractthepercentageoffemalesfrom100%.
Overall,thefindingsforprevalencerevealthatfemalecharacterswerevastlyunderrepresented
onscreeninthe100mostpopularmoviesof2014.Despitecomprisingroughly50%oftheU.S.
population,girls/womenmakeuplessthanathirdofallspeakingcharactersonscreenandless
thanaquarteroftheleads/coleadsdrivingthestorylines.Lessthanoneoutoffourcharactersin
animatedoractionadventuremovieswerefemale.Clearly,thenorminHollywoodistoexclude
girlsandwomenfromthescreen.Itisalsotomisrepresentthem,aswewillseeinthenext
section.
OnScreenPortrayal
Threespecificaspectsofcharacterportrayalswereevaluated:domesticroles,apparentage,and
sexualization.Focusingondomesticroles,speakingcharacterswereassessedforwhetherthey
wereshownasparents(no,yes)and/orinaromanticrelationship(no,yes).
Femalecharacters(53.5%)weremorelikelythanmalecharacters(41.9%)tobeshownas
caregivers.9Asimilartrendemergedforrelationalstanding,withfemales(59.6%)morelikely
thanmales(46.1%)tobedepictedinacommittedromanticrelationship.Thesepatternsreveal
thatdomesticatedrolesarestillgenderedinfilm,whichisconsistentwithpreviousresearch.10
Inadditiontodomesticroles,theapparentageofeachcharacterwasofinterest.Eachcharacter
wascategorizedintooneoffivemutuallyexclusivesilos:012years(child);1320years(teen);
2139years(youngadult);4064years(middleaged);or65yearsorolder(elderly).Table3
revealsthatcharactergenderandagewereassociatedacrossthe100topfilmsof2014.11
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
9
Aschildren,teens,andtheelderly,maleandfemalecharactersdonotdifferby5%.However,
females(57%)weremorelikelythantheirmalecounterparts(45.9%)tobedepictedasyoung
adults(i.e.,21to39yearsofage)whereasthereversewastrueforthoseinmiddleage
(Males=35.6%,Females=21.7%).

Table3
CharacterAgebyGenderinTopGrossingFilms:2014
ApparentAgeMalesFemales
012years5.4%
(n=164)
7.6%
(n=95)
1320years8.5%
(n=260)
9.6%
(n=120)
2139years45.9%
(n=1,402)
57%
(n=709)
4064years35.6%
(n=1,089)
21.7%
(n=270)
65+years4.6%
(n=140)
4%
(n=50)
Total100%100%
Note:Theanalysisrevealsthewithingenderdistributionofcharacterage.Thus,thecolumns
totalto100%.Rowpercentagesarenotshownbutcanbederivedfromcelltotals.
Thepreviousanalysisfocusedonthedistributionofcharacteragewithineachgender.Now,we
turntoassesshowgenderdistributeswithinoneparticularagegrouping:40to64yearolds.
FocusingontherowfrequenciesinTable3,themarginalizationof40to64yearoldfemales
becomesmoreapparent.Only19.9%of40to64yearoldswerewomenin2014.Giventhat
femalesinthisagegroupwerethemostunderrepresentedin2014,welookedatthegender
breakdownofcharacters40to64yearsofageacrossthefullsevenyearsample.
Across700films,atotalof9,522characterswerecodedbetween40to64yearsofage.Less
thanaquarter(21.8%)ofthesecharacterswerewomen.Thisisagenderratioof3.6middleaged
malestoevery1middleagedfemale.AsshowninTable4,therehasbeennoincreaseinthe
percentageoffemalespeakingcharacters40to64yearsofagefrom2007to2014.Thehighwas
observedin2008,however.Notonlydofemaleactorsfaceasteepfiscalcliffwhentheyreach
40yearsofageonscreen,buttheyarenotvaluedinthesamewayastheiryoungerfemale
counterparts.Thisbecomesapparentinthesectionbelow,whichexaminesphysicalattributes.
Table4
GenderofCharacters4064YearsofAge:20072014
Genderof4064yrolds2007200820092010201220132014Total
%ofmales 78.9%74.5%76%78.9%79.3%78.9%80.1%78.2%
%offemales 21.1%25.5%24%21.1%20.7%21.1%19.9%21.8%
Total#ofCharacters1,4611,1781,2871,3541,3831,5001,3599,522
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
10
Note:Thepercentageswithineachcolumntotal100%.
Threeappearancebasedindicatorsweremeasured.12Eachspeakingornamedcharacterwas
evaluatedforwearingsexuallyrevealingclothing(no,yes),exposingskininchest,midriff,upper
thighregions(nonudity,somenudity),andbeingreferencedasphysicallyattractive(no,yes)by
othercharacters.Allthreeofthesevariablesweresignificantlyrelatedtogender.Femalesofall
agesweremorelikelythanmalestobeshowninsexyattire(27.9%offemalesvs.8%ofmales),
withpartialorfullnudity(26.4%offemalesvs.9.1%ofmales)andreferencedasphysically
attractive(12.6%offemalesvs.3.1%ofmales).Thesetrendsareproblematic,astheorysuggests
andresearchsupportsthatexposuretoobjectifyingcontentcancontributetonegativeeffects
(e.g.,selfobjectification,bodyshame)amongsomefemales.13
Table5
HypersexualizationofFemaleCharactersOnScreen:20072014
Measures2007200820092010201220132014
%insexualizedattire27%25.7%25.8%33.8%31.6%30.2%27.9%
%w/somenudity21.8%23.7%23.6%30.8%31%29.5%26.4%
%referencedattractive18.5%15.1%10.9%14.7%Not
measured13.2%12.6%
Note:Thepercentageswithineachcolumndonottotal100%.Rather,eachcellreflectsthepercentageoffemales
depictedwiththemeasurereferenced.Forinstance,27%offemaleswereshowninsexualizedattirein2007.This
meansthat73%werenot.
Hastheleveloffemalesexualizationchangedovertime?Table5revealsthatverylittledeviation
hasoccurredacrossthesevenyearsample.Nodifferencesemergedonsexyattireornudity
whencomparing2007to2014.Thesevenyearhighonsexyattireandnuditywasobservedin
2010and2012,respectively.Between2007and2014,a5.9%declineintheproportionof
femalesreferencedasphysicallyattractivewasobserved.Asapointofcontrast,theovertime
percentagesofmalesexualizationacrossthesamethreeindicatorsareprovidedinTable6.This
tableshowsthatmalesexualizationisdramaticallylowerthanfemalesexualizationandthatthe
trendshavenotchangedbetween2007and2014.Malecharactersdepictedinsexyattireor
withexposedskinwereatahigh(9.7%,11.7%,respectively)in2013,butthesepercentagesdo
notdifferfrom2014percentages.
Table6
HypersexualizationofMaleCharactersOnScreen:20072014
Measures2007200820092010201220132014
%insexualizedattire4.6%5.1%4.7%7.2%7%9.7%8%
%w/somenudity6.6%8.2%7.4%9.4%9.4%11.7%9.1%
%referencedattractive5.4%4.1%2.5%3.8%Not
measured2.4%3.1%
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
11
Note:Thepercentageswithineachcolumndonottotal100%.Rather,eachcellreflectsthepercentageofmales
depictedwiththemeasurereferenced.Forinstance,4.6%ofmaleswereshowninsexualizedattirein2007.This
meansthat95.4%werenot.
Now,weturntoexaminetherelationshipbetweencharacterageandsexualization.Giventhe
pronouncedgenderdifferencesfoundabove,onlythefindingsforfemalecharactersare
reportedbelow.14Onlyteens,youngadults,andmiddleagedcharacterswereincludedinthe
analysis.ThesexualizationbyageresultsformalecharacterscanbefoundinFootnote15.As
illuminatedinTable7,femaleteens(13‐20yrolds)werejustaslikelytobeshowninsexyattire,
withexposedskinandreferencedasattractiveinthe100topfilmsof2014asyoungadultfemales
(21‐39yrolds).Middleagedfemaleswerelesslikelythantheothertwogroupstobesexualized.
Table7
FemaleSexualizationbyAgeinTopGrossingFilms:2014
Measures1320yrolds2139yrolds4064yrolds
%insexualizedattire 35.3%37.4%14.8%
%w/somenudity33.6%34.9%14.8%
%referencedattractive 20%16.1%5.2%
Note:Thepercentageswithineachcolumndonottotal100%.Rather,eachcellreflectsthepercentageoffemales
depictedwiththemeasurereferenced.Forinstance,35.3%of1320yroldfemaleswereshowninsexualizedattire.
Thismeansthat64.7%werenot.
Wetookadeeperdiveandlookedatthepercentageoffemalesinsexyattireandwithsome
nuditybyageinFigures1and2.Thetrendsareremarkablysimilarforbothmeasures.Whatis
particularlynotableisthecontinueddecreaseintheproportionof13to20yearoldfemalesin
sexyattireandwithsomenudityfrom2012to2014.However,thistrendistemperedbythefact
thatthepercentageoffemaleteensinsexyattirein2014isnotdifferentfrom2007.Also,
femaleteensin2014weremorelikelytobeshownwithexposedskinthanin2007.
Intotal,genderstereotypesarealiveandwellin2014topgrossingfilms.Femalesweremore
likelythanmalestobeyoungadults,sexualized,andshownindomesticatedrolessuchas
parentsandrelationalpartners.Someofthesepatternsinteractwithage,with13to20yearold
femalesand21to39yearoldfemalesequallylikelytobesexualized.Theclassofwomenmost
likelytobemarginalizedinmovieswaswomen40to64yearsofage.Thisisnosurprise,yetit
maycontributetoandreinforceageismandsexisminscreenwritingaswellasindustrycasting
andhiring.Further,thesepatternsmayperpetuateimplicitbiasesinviewers.
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
12
Figure1
PercentagesofFemalesinSexyAttirebyAge:20072014
Figure2
PercentagesofFemalesw/ExposedSkinbyAge:20072014
34.6%
39.8%
33.8%
41.4%
56.6%
40.5%
35.3%
37.7%
32.4% 33.5%
44.3%
39.9% 39.4%
37.4%
12.5%
14.9% 14.4%
22.6%
16.4%
18.8%
14.8%
10
30
50
70
2007 2008 2009 2010 2012 2013 2014
1320yrs
2139yrs
4064yrs
23.3%
30.1% 28.2%
33.0%
55.8%
37.4%
33.6%
31.2% 30.5% 30.5%
41.5%
39.6%
39.6%
34.9%
10.6% 14.2%
14.1%
19.7%
15.7% 18.5% 14.8%
10%
30%
50%
70%
2007 2008 2009 2010 2012 2013 2014
1320yrs
2139yrs
4064yrs
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
13
Table8
ContentCreatorsbyGender:2014
BehindtheCameraMalesFemalesTotal
Director98.1%(n=105)1.9%(n=2)107
Writer88.8%(n=262)11.2%(n=33)295
Producer81.1%(n=749)18.9%(n=175)924
Totals84.2%(n=1,116)15.8%(n=210)1,326
BehindtheCamera
Thegenderofalldirectors,writers,andproducerswasalsoevaluatedacrossthe100topfilmsof
2014.16Afull1,326individualsworkedbehindthecamerain2014.Only15.8%werefemaleand
84.2%weremale.Thiscalculatesintoagenderratioof5.3to1,whichisconsistentwithour
otherreportsontopgrossingfilms.17Lookingatspecificbehindthecameraposts,only2women
(1.9%)workedasdirectorsacrossthe100topfilms.Higherpercentageswereobservedfor
femalewriters(11.2%)andfemaleproducers(18.9%)in2014.Table9illuminatesthe
percentageandnumberoffemaledirectorsworkingacrossthe100topfilmsfrom2007to2014.
Across700filmsand779directors,only28women(3.6%)workedasdirectors.
Table9
NumberofFemaleDirectorsbyYear:20072014
Directors 2007200820092010201220132014Total
#offemaledirectors 394352228
%offemaledirectors2.7%8%3.6%2.75%4.1%1.9%1.9%3.6%
Total#ofDirectors112112111109121107107779
Wethenexaminedwhetherhavingatleastonefemalecontentcreatorbehindthecamerawas
associatedwithaselectnumberofvariables.Thetotalnumberofdirectorsacrossthe100top
grossing2014filmswastoolow(n=2)topermitstatisticalanalyses.Asaresult,weonlyfocused
onwritersandproducers.Eachfilmwasbifurcatedintotwocategories:thosewithatleastone
femalewriterattachedvs.thosewithnofemalewriters.Forproducers,thisprocedurewas
repeated.Then,therelationshipbetweenfemalewriter(no,yes)andfemaleproducer(no,yes)
andspecificvariableswasassessed.
Thefirstvariablewastheonscreengenderdistributionofspeakingroles.18Filmswithatleast
onefemalewriterhadasignificantlyhigherpercentageofgirlsandwomen(34.8%)onscreen
thandidfilmswithonlymalewriters(25.9%,seeFigure3).Thesefindingssuggestthatfemale
screenwritersmaybemorelikelytoincludegirlsandwomenintheirstorylinesthanmale
screenwriters,reflectingtheadage“writewhatyouknow.”Itmayalsobethecasethatfemale
writersaremorelikelytobehiredtopenfemaledrivenstories.Thelatterexplanationisclearly
problematicandreflectsapossibledoublestandardforcontentcreatorsbygender.No
differencesemergedinthepercentageofgirls/womenonscreenbyproducergender.
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
14
Figure3
WriterGender&PercentageofFemaleCharactersOnScreen
Next,wewereinterestedinwhetherthepresenceofafemalewriterorproducerchangesthe
genderdistributionofmiddleagedcharacters(4064yrolds).
19
Noassociationemergedby
producergender.However,a7.8%increasewasobservedinthepercentageofwomen40‐64
yearsofagewhenafemalewriterwasattached(25.9%femalesonscreenwithatleastonefemale
writervs.18.1%femalesonscreenwithnofemalewriters).
Finally,therelationshipbetweenfemalesexualizationandthepresenceofafemalewriterand
producerwasassessed.
20
Whilenodifferencesemergedforwritergender,thepresenceofa
femaleproducerwasassociatedwiththepercentageoffemalesdepictedinsexyattireandwith
someexposedskin.Incomparisontofemalecharactersinfilmswithoutafemaleproducer,
femalecharactersinfilmswithafemaleproducerwerelesslikelytobedepictedinsexually
revealingclothing(35.9%vs.26.4%)andwithsomenudity(33.3%vs.25.1%).
Thefindingsrevealthatfemalesaregrosslyunderrepresentedintopgrossingfilms.Females
wereoftenshownasdomesticated,young,andhypersexualized.Fewwomenworkbehindthe
camera.Whentheydo,however,theyareassociatedwithfilmsthatfeaturemorefemaleson
screen,alargerpercentageofwomen4064yearsofage,andlesssexualization.

34.8%
25.9%
0% 5% 10% 15% 20% 25% 30% 35% 40%
OneorMore
FemaleWriters
NoFemale
Writers
%offemalesonscreen
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
15
Race/EthnicityOnScreen&BehindtheCamera
OnScreenPrevalence
Eachyear,weexaminetheapparentrace/ethnicityofspeakingornamedcharacters.Atotalof
4,024characterscouldbeevaluatedforapparentrace/ethnicityacrossthe100topfilmsof
2014.Ofthese,73.1%wereWhite,4.9%wereHispanic/Latino,12.5%wereBlack,5.3%were
Asian,2.9%wereMiddleEastern,<1%wereAmericanIndian/AlaskanNativeorNative
Hawaiian/PacificIslander,and1.2%werefrom“other”racialand/orethnicgroupings.Asshown
inTable10,thisrepresentsnochangeintheportrayalofapparentrace/ethnicityfrom2007‐2014.
Table10
CharacterRace/EthnicityinTopGrossingFilms:20072014
YearWhiteHispanicBlackAsianOther
200777.6%3.3%13%3.4%2.5%
200871.2%4.9%13.2%7.1%3.5%
200976.2%2.8%14.7%4.7%1.5%
201077.6%3.9%10.3%5%3.3%
201276.3%4.2%10.8%5%3.6%
201374.1%4.9%14.1%4.4%2.5%
201473.1%4.9%12.5%5.3%4.2%
Note:OthercomprisesMiddleEastern,AmericanIndian/AlaskanNative,NativeHawaiian/Pacific
Islanderaswellasthosewithmixedracial/ethnicheritages.
Table10statisticscanbeexaminedagainstU.S.CensusBureaufigures.IntermsofU.S.
populationestimatesfor2013,Hispanicscomprised17.1%ofthepopulation,Blacks13.2%,and
Asians5.3%.21Inlightoftheserealworldpercentages,Hispanic/Latinocharactersonscreenin
filmcontinuetobethemostunderrepresentedethnicgroup.Thisissurprisinggiventhat
Hispanicspurchased23%ofU.S.movietickets22in2014andNielsen(2014,¶1)estimatesthat
they“haveacurrentspendingpowerofabout$1.4trillion.”23
IntheU.S.,individualsfromunderrepresentedracialand/orethnicgroupsamountto37%ofthe
populationand,in2014,bought46%ofmovieticketsattheboxoffice.24Acrossthe100topfilms
of2014,underrepresentedcharactersaccountedfor26.9%ofallspeakingornamedcharacters.
Further,only17ofthe100topfilmsof2014featuredaleadorcoleadactorfroman
underrepresentedracialand/orethnicgroup.Ofthe17leads,47%wereBlack,29.4%werefrom
mixedracial/ethnicheritages,11.8%wereAsian,and11.8%wereHispanic/Latino.Anadditional
3filmsdepictedanensemblecastwith50%ormoreofthegroupcomprisedofactorsfrom
underrepresentedracial/ethnicbackgrounds.
Similartoearlierinthereport,welookedatthepercentageofallunderrepresentedcharacters
inaction/adventure,animation,andcomedy.AsshowninTable11,no5%orgreaterdifferences
emergedinthepercentageofunderrepresentedcharactersonscreeninaction/adventureor
comedyfrom2007or2010.Whencomparedto2007a25.4%increaseinthepercentageof
underrepresentedcharacterswasobservedinthetopanimatedfilms(n=10)of2014.Overhalfof
thesecharactersappearedinoneanimatedfilm,TheBookofLife.Evenwithoutthismovie,thereis
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
16
stillasignificantincreaseinthepercentageofunderrepresentedspeakingcharactersinanimated
filmsfrom2007to2014.
Table11
PercentageofUnderrepresentedCharactersbyFilmGenre:2007,2010,2014
Actionor
AdventureAnimationComedy
200720102014200720102014200720102014
%ofunderrepresented
charactersonscreen21.5%29.7%26.1%8.1%1.5%33.5%23.1%23.8%26.5%
Note:OnlythepercentageofunderrepresentedspeakingornamedcharactersisreportedinTable11.Forthe
percentageofWhitespeakingcharacters,subtractthepercentageofunderrepresentedcharactersfrom100%.
Giventhatanoverallpointstatisticdoesnotrevealhoweachfilmportraysdiversity,itbecomes
importanttoexaminethepercentageofunderrepresentedcharacterspermovie.Since37%of
theU.S.populationisnotWhite,weassessedwhatnumberofmoviesfellwithin+/5%pointsof
thispointestimate(32%42%).Only14%offilmsfeaturedunderrepresentedcharactersin32%
42%ofthecast.Moreproblematically,in19movies10%orlessofthecastwasfrom
underrepresentedracial/ethnicgroups.
Yearly,wealsoreportonthefrequencyofBlackcharactersonscreen(seeFigure4).In2014,
12.5%ofallspeakingornamedcharacterswereBlack.However,afull17filmsdidnotfeature
oneBlackspeakingornamedcharacter.Thispercentageisidenticaltolastyear.Only11%of
filmsinthe2014samplefeaturedBlackcharactersinapercentagethatfellcloseto(+/2%)U.S.
Census(13.2%).NinepercentofallfilmsdepictedBlackcharactersas30.1%62%ofthecast.
Figure4
PercentageofBlackCharactersperMoviein100TopGrossingFilms:2014
17%
24%
23%
11%
15% 9% NoBlackCharacters
1.6%6%ofCharsareBlack
6.9%11.1%ofCharsareBlack
11.2%15.2%ofCharsareBlack
15.3%30%ofCharsareBlack
30.1%62%ofCharsareBlack
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
17
InadditiontoBlackcharacters,weexaminedthedistributionofAsiancharactersperfilm.Atotal
of5.3%ofspeakingcharacterswereAsiansamplewideacrossthe2014topfilms(seeTable10).
Justoverafifth(n=21)ofthe2014filmsarewithin+/2%oftheU.S.Censusfigureof5.3%,
whichisidenticalto2013films(n=21).However,over40ofthe100mostpopulardomestic
moviesof2014featurednoAsianspeakingcharactersonscreen.Thisfindingisnotdifferentfrom
2013.Six2014filmsfeatureAsiancharactersin20%45%ofthecast.
Turningtogender,thepercentagesofmalesandfemaleswithinthemajorracial/ethnic
categoriesacrossthe100topgrossingfilmsof2014arereportedinTable12.Character
race/ethnicitydidnotvarysignificantlybygender(seeTable12).
Table12
CharacterRace/EthnicitybyGenderinTopGrossingFilms:2014
WhiteHispanicBlackAsianOther
Males70.5%68.5%69.2%67.4%75.1%
Females29.5%31.5%30.8%32.6%24.9%
Ratio2.40to12.18to12.24to12.07to13.02to1
Note:OthercomprisesMiddleEastern,AmericanIndian/NativeAlaskan,NativeHawaiian/PacificIslanderas
wellasthosewithMixedracial/ethnicheritages.
Overall,theresultsshowthatunderrepresentedcharacterslackvisibilityonscreeninpopular
films.Further,therehasbeennomeaningfulchangeinracial/ethniccompositionofcastsover
thesevenyearsevaluated.Apromalebiaspersistsacrosseveryracial/ethnicgroupexamined,
particularlyamongcharactersfrommixedraceor“other”ethnicheritages.
OnScreenPortrayal
Focusingonportrayals,welookedattherelationshipbetweencharacterrace/ethnicityand
domesticroles(parental,relationalstatus)aswellasourappearanceindicators.Giventhe
genderdifferencesnotedabove,theanalyseswererunseparatelyformalesandfemalesonall
measuresinthissection.Parentalstatusandrelationalstandingdidnotstatisticallyvaryby
characterrace/ethnicityformalesorfemalesin2014.
Turningtoappearancemeasures,onlyone(attractiveness)ofthethreemeasureswas
statisticallyrelatedtorace/ethnicityforfemalecharacters(Table13).25Incomparisonto
Hispanic/Latinofemales(9.7%),Whitefemalesweremorelikelytobereferencedasphysically
attractivewhereasAsianfemalesandfemalesfrom“other”racial/ethnicgroupswerelesslikely.
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
18
Table13
HypersexualizationofFemaleCharactersbyRace/Ethnicity:2014
MeasureWhiteHispanicBlackAsianOther
%insexyattire27.5%30.6%29%25.7%31%
%w/exposedskin26.3%27.4%27.7%20%31%
%referencedattractive 14.8%9.7%11.6%4.3%2.4%
Note:OthercomprisesMiddleEastern,AmericanIndian/NativeAlaskan,NativeHawaiian/PacificIslanderaswellas
thosewithMixedracial/ethnicheritages.Columnsdonottotalto100%.Rather,eachcellreflectsthepercentageof
femalesdepictedwiththemeasurereferenced.Forinstance,27.5%ofWhitefemaleswereshowninsexualized
attire.Thismeansthat72.5%ofWhitefemaleswerenot.
Incontrast,allthreeappearancemeasureswereassociatedwithmalecharacters’
race/ethnicity.26WhencomparedtoHispanics/Latinos,Blackand“other”malecharacterswere
morelikelytobeshowninsexuallyrevealingattire.AsianmaleswerelesslikelythanWhite,
Blackandmalesfrom“other”racial/ethnicgroupstobeshowninsexyclothing.Whencompared
toBlackandWhitemales,thosefrom“other”racial/ethnicgroupsweremorelikelytobeshown
withexposedskinandAsianmaleswerelesslikely.Hispanic/Latinomaleswerelesslikelythan
thosemalesfrom“other”racial/ethnicgroupstobeshownwithsomenudity.Finally,Black
malesweremorelikelythanAsianmalestobereferredtoasphysicallyattractive.
Table14
HypersexualizationofMaleCharactersbyRace/Ethnicity:2014
MeasureWhiteHispanicBlackAsianOther
%insexyattire7.2%6%11.8%1.4%11.1%
%w/exposedskin9.4%6%7.8%2.1%18.9%
%referencedattractive 2.7%3.7%5.7%.7%2.4%
Note:OthercomprisesMiddleEastern,AmericanIndian/NativeAlaskan,NativeHawaiian/PacificIslanderaswellas
thosewithMixedracial/ethnicheritages.Columnsdonottotalto100%.Rather,eachcellreflectsthepercentageof
malesdepictedwiththemeasurereferenced.Forinstance,7.2%ofWhitemaleswereshowninsexualizedattire.
Thismeansthat92.8%ofWhitemaleswerenot.
BehindtheCamera
Asilluminatedabove,107directorshelmedthe100topfilmsof2014.Only5(4.7%)ofthese
directorswereBlack(seeTable15).Thefivefilmstheydirectedinclude:RideAlong(TimStory),
TheEqualizer(AntoineFuqua),ThinkLikeaManToo(TimStory),Selma(AvaDuVernay),and
WhentheGameStandsTall(ThomasCarter).Asthislistillustrates,onlyfouruniqueBlack
directorsworkedacrossthetopfilmsof2014.Only1wasaBlackfemaledirector.
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
19
Table15
NumberofBlackDirectorsbyYear:20072014
BlackDirectors 2007200820092010201220132014Total
%ofmale
directors
7.1%
(n=8)
4.5%
(n=5)
6.3%
(n=7)
4.6%
(n=5)
4.9%
(n=6)
6.5%
(n=7)
3.7%
(n=4)
5.4%
(n=42)
%offemale
directors01.8%
(n=2)0000<1%
(n=1)
<1%
(n=3)
Total#ofDirectors112112111109121107107779
Tocontextualize2014,wehavepresentedthenumberandpercentageofBlackdirectorsfrom
2007to2014(seeTable15,excluding2011).Only45(5.8%)Blackdirectorshavebeenattached
tothe700topgrossingfilms,whichunderindexesincomparisontoU.S.Census(13.2%).Only3
Blackdirectorswerewomenacrossthe700topgrossingfilmsof20072014.
Figure5
PercentageofBlackCharactersbyDirectorRace
Next,wewereinterestedinhowthepresenceorabsenceofaBlackdirectorwasassociatedwith
thepercentageofonscreencharactersinfilmthatwereBlack.AsshowninFigure5,the
relationshipbetweendirectorraceandcharacterracewaspronounced.27Ofthefilmswitha
Blackdirector,40.2%ofallcharacterswereBlack.WhenthedirectorwasnotBlack,only10.6%
ofallonscreenspeakingornamedcharacterswereBlack.
Thesefindingsaresimilartoearlierresultsinthereportonfemalewriters.Blackdirectorsmay
betellingstoriesthatreflecttheirsocialandculturalexperiences.Or,itmaybethecasethat
BlackdirectorsgethiredtohelmfilmsthathaveprimarilyBlackcasts.Asmentionedearlier,this
latterexplanationisproblematicasitlimitstheworkopportunitiesfordirectorsbythe
racial/ethniccompositionoftheleadorsupportingcast.
10.6%
40.2%
0% 10% 20% 30% 40% 50%
BlackDirectorAbsent
BlackDirectorPresent
%ofBlackCharactersOnScreen
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
20
InadditiontoexaminingBlackdirectors,thisyearweassessedAsiandirectorsworkingacrossthe
700movies.AsshowninTable16,only19Asiandirectorsworkedacrossthe700topfilmsof
2007,2008,2009,2010,2012,2013,and2014.Thistranslatesintoonly2.4%ofalldirectors.
Only1Asianwomanwasattachedasacodirectorforaspecificregion(India)onSlumdog
Millionaire.
Table16
NumberofAsianDirectorsAcross700Films
AsianDirectors 2007200820092010201220132014Total
%ofmale
directors
2.7%
(n=3)
1.8%
(n=2)
<1%
(n=1)
3.7%
(n=4)
1.6%
(n=2)
5.6%
(n=6)02.3%
(n=18)
%offemale
directors0<1%
(n=1)00000<.2%
(n=1)
Total#ofDirectors112112111109121107107779
Overall,atleastthreenotablefindingsemergedfromthissection.First,filmisstillaWhite
bastion.Second,asubstantialincrease(25.4%)wasobservedinthepercentageof
underrepresentedcharactersinanimatedfilms.Someofthatwasduetothediversityinthefilm
TheBookofLife.Third,fewBlackorAsiandirectorsworkinthetopgrossingsphere.Onlythree
BlackfemalesandoneAsianwomandirectedmoviesassessedinthisanalysis.Blackdirected
movieswereassociatedwithmoreBlackcharactersonscreen,afindingwehaveobservedinour
previousresearch.
LGBTOnScreenPortrayals
Forthefirsttime,theMDSCInitiativeaddedqualitativemeasurestocapturetheprevalenceof
Lesbian,Gay,Bisexual,and/orTransgender(LGBT)charactersonscreen.28Acrossthe4,610
speakingornamedcharactersonscreen,only19werecodedasLGBacrossthe100topfilmsof
2014.29Thisislessthanhalfof1%ofallportrayals(.4%).TencharacterswerecodedasGay,4
wereLesbian,and5wereBisexual.NotoneTransgendercharacterwasportrayed.Only14
moviessamplewidefeaturedanLGBdepictionandnoneofthosefilmswereanimated.
ThepercentageofLGBcharactersisnotablylowerthanestimatesoftheLGBpopulationinthe
U.S.,whichTheWilliamsInstituteatUCLAreportstobe3.5%and0.3%identifyingas
Transgender.30Inamorerecentstudyof1835yearoldsintheU.S.,“sevenpercentof
millennialsidentifyeitheraslesbian,gay,bisexual,ortransgender(LGBT)”(PRRI,2015,seepage
46,¶1).31Clearly,HollywoodissubstantiallyunderindexingoninclusiveportrayalsoftheLGBT
community.
Whatisthegenderandracial/ethnicbreakdownofthe19LGBcharacters?Nearlytwothirds
weremale(63.2%)andonly36.8%werefemale.LGBcharacterswerealsopredominantlyWhite
(84.2%or16Whitecharacters,10.5%or2Asiancharacters,5.3%or1Blackcharacter).Interms
ofage,themajorityofcharacterswereyoungadultsorolder(n=17).Twofemalecharacters
wereteens.Itmustbenotedthatonecharacter(AlanTuring,TheImitationGame)wasdepicted
inaflashbackduringhisteenageyears.
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
21
ThreetrendswereapparentinportrayalsofLGBcharactersinthetopgrossingfilmsof2014.
First,depictionsofhealthyromantic/sexualrelationshipswerescarce.Of19LGBcharacters,only
twowereportrayedasbeinginapublic,stable,longtermpartnershipandtwowereshown
dating.Notably,thesecharactersrepresentedinterracial(Asian/White)Lesbiancouples.
However,noGayorBisexualmalecharacterswereportrayedinacommittedrelationship.
Second,noLGBcharactersweredepictedasparentsraisingyoungchildrentogether.Finally,a
handfulofGayandBisexualcharacterswereshownconcealingtheirsexuality.
Conclusion
Thelandscapeofpopularcinemain2014remainsskewedandstereotypical.Across700films
andover30,000speakingcharactersfrom2007topresent,moviescontinuetodistortthe
demographicrealityoftheiraudience.FilmcharactersareoverwhelminglyWhiteandmale,
despitebothpopulationstatisticsandviewingpatterns.
Employmenttrendsbehindthecameraevidenceasimilardearthofdiversity.OnlyfiveBlack
directorshelmedtopmoviesin2014,andwomenwereunderrepresentedbyafactorof5.3to1
asdirectors,writers,andproducersin2014.Further,the100topfilmsof2014featurednoAsian
directors.Despiteactivism,attention,andstatementsaboutaddressingtheissue,Hollywood’s
defaultsettingforcharactersandcontentcreatorsremainsfixedon“statusquo.”
Theportrayalofcharactersinpopularfilmisalsoproblematic.Moviesdepictfemalecharacters
asyoungerandmoresexualizedthantheirmalecounterparts.Thisfocusonyouthandbeauty
restrictsboththecareeropportunitiesoffemaleactorsandtherangeofstoriesthataretold.
Marginalizingmiddleagedwomenmeansmissingoutonplotsaboutfemalecharactersableto
achieveoccupationalorotherformsofpower.Increasingtheprevalenceoffemalesofallages
meansincreasingthevarietyofstoriesseenonscreen.
Intermsofdiversity,thepercentageofunderrepresentedcharactersinanimatedfilmsincreased
in2014.Overhalfofthesecharactersappearedinjustonemovie,TheBookofLife.However,
evenwithoutthisfilm,asignificantincreasewasobservedinthepercentageof
underrepresentedcharactersfrom2007to2014.Asagenredesignedtoappealtoyoung
viewers,animatedfarehasunderrepresentedthediversityofU.S.children.Halfofchildren
underage5arefromanunderrepresentedracialand/orethnicgroup.32Thoughitstarget
audienceisincreasinglydiverseanditsstoriesrestrainedonlybytheboundariesofimagination,
animatedcontentremainsanarenawhererepresentationandvisionlags.Itwillbeimportantto
examinethepercentageofunderrepresentedcharactersin2015moviestoassesswhetherthese
2014findingswereananomalyorpartofanewinclusivetrend.
After7yearsand700films,itisclearthatactivismandadvocacyarestillrequired.Reframingthe
requestsmadetowritersanddecisionmakersmaybeonewayforward.Theresultsfromthis
studyilluminatethatthreequarters(76%)ofthecharactersinpopular2014filmsare
inconsequentialtotheplot.Addingandadjustingthebackgroundorsupportingplayersisone
easyandessentialmeansofincreasingthediversityinpopularmovies.Doingsowillensurethat
theleadcharactersinpopularfilmsmovethroughademographiclandscapethatmatchesthe
profileoftheaudience.
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
22
Thepresentstudyhasseverallimitationswithregardtothescopeofthesemeasures.First,the
LGBTmeasureswereonlyappliedin2014.Thus,wehavelittleinformationonhowportrayals
havechangedovertimeinthe100topfilmsfrompreviousyears.Asaresult,weplantomonitor
thesedepictionsqualitativelyandquantitativelyinfuturestudies.Second,bothforonscreen
andbehindthecamera,theracialandethnicclassificationsareverybroad.Thoughderivedfrom
U.S.Censuscategories,manydifferentgroupsidentifywithineachlabel.Forinstance,theAsian
categoryencompassesmanyuniqueethnicgroups.Acloserexaminationofrepresentationof
individualethnicbackgroundsisneededinthefuture.Third,ourresearchdoesnotaddress
issuesofneurodiversityorphysicalabilities.In2016,weplantobeginexploringtheseother
formsofdiversityinmedia.
Lookingaheadto2015,changemayalreadybeonthehorizon.Filmsbyandaboutwomen(e.g.,
PitchPerfect2,Spy,FiftyShadesofGrey,Cinderella,Insurgent)havedrawnticketbuyersen
masse.Fivefemaledirectorshavehelmedfilmsthatmadeover$25millioninthefirsthalfof
2015,whichshouldputthemallinthe100topfilmsthisyear.Thisisgreaterthanthenumberof
femaledirectorsofthe100topfilmsof2013and2014.Diversityhasalsoproventobeadrawat
theboxoffice,withfilmslikeFurious7earningover$1billionworldwide.Whiletheeconomics
areencouraging,longtermsolutionsandfurthermonitoringarerequired.Onlywithsustained
effortandchangecanHollywoodmovefromanindustryofinequalitytooneofinclusion.
StudyfundedbyTheHarnischFoundation&supportersofMDSCInitiative©Dr.StacyL.Smith
23
Notes
1.Thelistof100topgrossingfilmsof2014wascompliedfromBoxOfficeMojo(http://www.
boxofficemojo.com/).Therevenueswerebasedondomesticboxofficeperformance.Nodocumentarieswere
includedinthe100topfilms.Assuch,thestudyonlyfocusesonfictionalfeatures.
2.Becausethisisalongitudinalinvestigation,thelanguageregardingvariables,definitions,training/reliability,and
codingproceduresistakenfromourcodebookandthusthefootnotesarehighlysimilarfromyeartoyear.There
weretwounitsofanalysisinthepresentstudy:thespeakingcharacterandthefilm.Acharacterisdefinedasaliving
beingthatspeaksoneormorewordsindependentlyanddiscerniblyonscreen.Nonspeakingcharactersthatare
referredtobynamealsowereincludedintheinvestigation.Sometimescharactersappearnearlyidenticaland
speakindependentlyonscreen.Inthesecases,theuniqueidentityofcharactersmaynotbedecipherable.When
thisoccurs,thecoders“group”homogeneouscharactersandcodethemasasingleentity.Thishappens
infrequentlyacrossthe100topfilms.Only6groupswerefoundacrossthesampleofmoviesthisyear,whichis
lowerthanwhatwefoundin2013(n=30)butconsistentwithotheryearswehavereported(e.g.,n=3in2012;n=9
in2010).Allgroupdatawasexcludedfromanalysis.Anytimeanindependentspeakingcharacterchangedtype,age,
sex,orethnicity,anewcharacterlinewascreated.Atotalof236demographicchangeswereobservedacrossthe
sample;ifthesewereremovedthepercentageoffemalecharacterswoulddecreaseby.1%to28%.Thus,
demographicchangeshaveverylittleimpactontheoverallpercentageofspeakingcharactersbygender.
3.Eachcharacterwasevaluatedonaseriesofdemographiccharacteristics:sex(male,female);age(05years,612
years,1320years,2139years,4064years,65+years);apparentrace/ethnicity(White,Hispanic/Latino,Black,
AmericanIndian/AlaskanNative,NativeHawaiian/PacificIslander,Asian,MiddleEastern,Other);androle(primary,
secondary,tertiary).Characterswerealsoassessedforparentalstatus(notaparent,singleparent,coparent,
parentrelationalstatusunknown)andrelationalstatus(single,married,committedrelationshipnotmarried,
committedrelationshipmartialstatusunknown,divorced,widowed).Theselattertwomeasureswereonlyassessed
whentherewasenoughinformationavailabletomakeajudgment.Asaresult,thesamplesizeofcharactersfor
thesetwoanalysesismuchsmaller.
Therewerethreeappearanceindicators,whichwerederivedfromDowns&Smith(2010,p.725).Sexuallyrevealing
clothing(SRC)referstotightorrevealingapparelworninsuchawaythatheightensand/ordrawsgazetopartsof
thebodyfrommidchesttomidthigh.SRCwascodedaspresentorabsent.Nudityreferstotheamountofskin
shownduetothelackofclothingoritsinsufficientcoverageofspecificbodyparts.Nudity(Downs&Smith,2010,p.
725)wascodedasnone,partial(i.e.,skindepictedinbreast,midriff,and/orlowerbuttocksregions),orfull(i.e.,
exposedbreast(s)orgenitalsforfemales;exposedgenitalsonlyformales).Abarebuttockisnotconsideredfullbut
ratherpartialnudity.Also,fullnudityiscodedifcharactersareshownwithoutanyclothesbutusetheirhandsto
coverbreastand/orgenitalregions(e.g.,TheProposal).Thesevariableswereonlyassessedforcharacterswith
humanorhumanlikebodies.
Characterswerealsoassessedforattractiveness,whichdemarcatesthefrequencyofverbal(e.g.,“heishot!”)
and/ornonverbalreferences(e.g.,making“eyes”atanothercharacter)one(ormore)charactermakesabout</