Gender Gap
Running Head: The Political Gender Gap in the 1996 Presidential Election
Beyond Sex: The Political Gender Gap
in the 1996 Presidential Election
B. Carol Eaton
Doctoral Student
S. I. Newhouse School
of Public Communications
Syracuse University
215 University Place
Syracuse, New York 13244
[log in to unmask]
(315) 443-1950 (work)
(315) 423-2965 (home)
Abstract
A telephone survey of Syracuse, New York, residents was conducted in
October/November 1996 to test the study's hypotheses regarding the political
gender gap and media sources utilized to obtain political information. The fact
that this study's results failed to replicate previous political gender gap
findings is significant. Findings demonstrate that the historical distinction
between traditionally "male" and "female" political issues may be changing in
today's political climate. This analysis also successfully developed a reliable
gender scale which extends conventional telephone survey research methodology.
By showcasing dozens of women in such prominent roles as keynote speakers and
chairwomen at the Republican and Democratic conventions, both political parties
delivered deliberate appeals to female voters for the 1996 U. S. presidential
campaign. Indeed, a pre-election New York Times article described both parties
as "believ[ing] that the election will ultimately be decided by the women's
vote" (Nagourney, 1996, p. A1). Identified by some strategists as "soccer
moms," suburban women swing voters were targeted by both the Democratic and
Republican candidates (Frisby & Seib, 1996, p. A4).
Polls conducted during the convention reported Clinton ahead of Dole by margins
of six and sixteen percent among male and female voters, respectively; a gender
gap that one democratic pollster hoped to transform "into a gender canyon -- and
put the race out of range" (Nagourney, 1996, p. A1). The "gender gap" between
female and male voting patterns was first identified during the 1980
presidential election, when eight percent more men than women voted for Ronald
Reagan (Abzug, 1984, p. 1). Although a plethora of scholarly books and articles
addressing this political gender gap appeared during the decade that followed
its identification, research on this area has been sparse over the past five
years.
Another important development during this decade that has remained relatively
unexamined by scholars concerns the emergence of new media vehicles for
political campaigns. During the 1992 presidential campaign, candidates appeared
in many unusual media milieus, including daytime talk shows, infomercials, and
MTV programs. One political scientist describes a recent explosion of new media
information outlets producing "new opportunities for politicians to reach out to
constituents, sometimes in unconventional ways" (Kerbel, 1995, p. 3).
This study seeks to identify how the political gender gap manifests itself in
the new media environment of the 1996 presidential election.
Theory
Political Gender Gap
The phenomenon labeled "gender gap" describes the pronounced differences
between male and female voting behaviors that have emerged in the United States
over the past fifteen years. This gap was first identified during the 1980
election when eight percent more women than men voted for Jimmy Carter and eight
percent more men than women voted for Ronald Reagan (Kelber, 1994).
According to Baxter and Lansing, "the term gender gap...became part of the
political vernacular during the 1982 election [when] the women's vote made the
difference in a number of close races" (1983, p. 212). These voting differences
have continued into this decade. In the 1994 congressional elections, for
example, "women gave Democrats an eight-point margin, while men picked
Republicans by 14 points" ("Gender Gap Politics," 1995, p. 22).
In the early 1980s, many scholars explored these nascent female voting
patterns. In Women and Politics: The Visible Majority, Baxter and Lansing
(1983) compared contemporary characteristics of female voters to historical U.
S. trends. Discriminant analysis revealed employment status and age as the most
important predictors of female voting behaviors, demonstrating that "the voters
who produced the gender gaps in 1980 and 1982 were not simply women, but were
likely to be professional working women over the age of thirty (Baxter &
Lansing, 1983, p. 185). Women with higher income and education levels were also
more likely to vote (Baxter & Lansing, 1983).
Abzug (1984) characterized stronger gender gap voting patterns among
southerners, African-Americans, Catholics, Jews, professionals, college
graduates, democratic and independent political affiliations, and 30 to 44 year
olds. The current study will develop similar controls for the following voter
demographics: age, employment status, education, income, race, ethnicity,
religion, and party affiliation.
Abzug partly explains the gender gap in terms of women's support of political
issues that reflect "the distinctive political voice of women" (1984, p. 5).
These issues include the reduction of military spending and unemployment, the
advancement of world peace and women's rights, assistance to the poor, and
protection of the environment (Abzug, 1984). In the early 1980s, women were
more likely to vote democratic and support world peace, environmental
preservation, and "women's" issues (e.g., the Equal Rights Amendment and
abortion) than men (Baxter & Lansing, 1983). Over the last decade, scholars
have continued to specify the political issues that are most closely associated
with gender gap voting patterns. In contrast to men, women tend to be more
supportive of social programs, racial equality, legislation to resolve social
problems, job security, alternatives to nuclear power, international peace, and
education (Abraham, 1995; Fitzpatrick, 1995; Huddy & Terkildsen, 1993; Kelber,
1994; Mandel, 1995; Mueller, 1991; Somma, 1992).
Welch and Hibbing (1992) have classified these gender gap political issues into
two categories: sociotropic and egocentric voting patterns. Using secondary
data from the 1980 and 1984 National Election Study surveys, Welch and Hibbing
(1992) found that men were more likely to base their voting decisions on
egocentric economic factors (e.g., concern for personal economic well-being)
while women tended to rely on sociotropic economic influences (e.g., concern for
the nation's financial health). These results persisted after controlling for
partisanship, education, and income. The authors conclude that, "the gender gap
encompasses more than just having slightly dissimilar political attitudes; it
also includes a different way of using these attitudes to provide a basis for
political action" (Welch & Hibbing, 1992, p. 210).
Other scholars have also identified sociotropic voting patterns as an
explanation of the political gender gap. According to Abzug (1984), the
political gender gap developed when women began to extend their long-standing
personal (private) values of non-violence and nurturing into their political
(public) views. The socialization of females in care-giving roles may have
created this "compassion" gap which leads to sociotropic voting patterns among
women (Gilligan, 1982; Miller, 1988; Norris 1985; Somma, 1992). Similar to this
previous body of research, the current study will examine the potential gender
gap in the 1996 presidential election in terms of these sociotropic and
egocentric political issues.
Another factor that may explain the emergence of the gender gap concerns the
social and economic position of women in society: "Changing material conditions
in motherhood, marriage, and work underlie the politicization of women and
gender group consciousness (Klein, 1984, as cited in Somma, 1992, p. 44). Over
the past 35 years, U. S. Census data has shown a marked increase in the number
of employed women in the workforce. Recent voting trends, indeed, appear to
reflect these changing female demographics: In the 1980s, employment status and
age supplanted education for the first time in the history of women's voting
patterns as more important predictors of voting behavior (Baxter & Lansing,
1983). As mentioned previously, this study will examine voter demographics in
relation to sociotropic and egocentric political issues in the 1996 election.
A third factor that may have contributed to gender gap voting patterns concerns
the emergence of women's "politicized gender consciousness" (Somma, 1992, p.
43). Feminist scholarship is based on "a theoretical acknowledgment of women's
traditional devaluation . . . in relation to men with the assumption that the
relationship needs to change" (Steeves, 1987, p. 96). Over the past thirty
years, the second wave of the women's movement has worked towards identifying
women's oppression in order to promote change (Boles, 1991). Contemporary
voting patterns among women may reflect this influence from the women's movement
and feminist scholarship.
The political gender gap has been described as the tendency of women to vote
democratic and for women candidates (Mandel, 1995); to favor sociotropic issues
(Somma, 1992); and to vote in higher numbers than men (Mueller, 1991). After
1980, scholars also identified a "gender gap in presidential campaign discourse"
where Republicans were more likely to refer to "men" and "man" and less likely
to refer to "societal values" than Democrats in campaign speeches (The Annenberg
Public Policy Center, 1996). The current study will examine the potential
gender gap in the 1996 presidential election in relation to voter demographics
and issue salience.
Gender and Sex Roles
Scholarly research on the political gender gap has equated the terms gender and
sex as if they were interchangeable: For most social scientists, both terms
refer exclusively to the biological differences between women and men. Recent
criticisms of this traditional approach have recognized that:
Gender is not limited to femaleness and maleness, but includes
men, masculinity, and manliness as well as women, femininity, and
womanliness. Gender extends to normative sets of beliefs, which
can be considered as feminism and masculinism. Masculinism is
more than a way of being; like feminism, it can be considered as
an ideology (Duerst-Lahti & Kelly, 1995, p. 5).
The current study will attempt to extend the political gender gap literature to
examine this concept of gender rather than biological sex differences among men
and women.
From the psychological literature, four theories of gender development have
evolved: psychoanalytic theory, social learning theory, cognitive development
theory, and gender schema theory (Bem, 1984). Based on Freud, psychoanalytic
theory describes an individual's gender identification and sexualization as
socially and culturally created in the unconscious mind through comparison with
a same-sex parent (Chodorow, 1989). Psychoanalytic feminist theory has extended
Freud's work to describe the importance of mothering in the creation of
"nurturant moral models" among women (Chodorow, 1978, p. 5).
In contrast, social cognitive theory emphasizes how gender identification is
acquired through observational learning from the external environment (Bandura,
1994). A child identifies appropriate gendered behavior through a "triadic
reciprocal causation" model that links cognition/internal events, behavior, and
the social environment (Bandura, 1994, p. 61).
Cognitive-development theory assumes that sex typing inevitably occurs from
children's cognitive development; this theoretical approach almost exclusively
identifies the individual child as his or her primary sex-role socialization
agent (Bem, 1984). Following the formulation of a gender-based self-concept,
the child seeks gender-congruent attributes and activities (Kohlberg, 1966).
Gender schema theory synthesizes selected features of the social learning and
cognitive-development approaches: "Sex typing is mediated by the child's own
cognitive processing" in the context of "sex-differentiated practices of the
social community" (Bem, 1984, p. 186). Gender schema are cognitive processing
patterns or associational networks that organize individual perceptions about
others and self in terms of gender (Hitchon & Chang, 1995). These schema can be
"primed" or activated by external stimuli like the media (Jo & Berkowitz, 1994).
In order to measure masculinity and femininity, Bem developed the Bem Sex Role
Inventory (BSRI) to classify respondents' gender based on forty personality
traits; "20 of the attributes reflect the culture's definition of masculinity
(e.g., assertive, independent), [and] 20 reflect the culture's definition of
femininity (e.g., tender, understanding)" (Bem, 1984, p. 192). Critics of the
BSRI and other similar instruments contend that these questionnaires only
measure, stereotypically and through self-report, two personality
characteristics rather than more universal theoretical concepts of masculinity
and femininity (Spence, 1984). Other criticisms describe how the "broad
multidimensional concepts [of femininity and masculinity] are not readily
captured in either one- or two-dimensional questionnaires" (Deaux, 1985, p. 59).
The current study concedes these limitations of measuring a respondent's gender
through survey research; however, a gender scale of masculine and feminine
traits presents a vast improvement over the mere measurement of biological sex
prevalent among most quantitative research methodologies. Based on various
gender trait analyses utilized in previous research (Bem, 1984; Diamond &
Harstock, 1981; Hitchon & Chang, 1995; Huddy & Terkildsen, 1993; Somma, 1992;
Welch & Hibbing, 1992), this study will develop a gender scale to measure
respondents' personality traits that describes gender in terms of the
"socially-ascribed meanings given to the categories of man and woman" (de Bruyn,
1995, p. 12).
Politics and Media Sources
The use of media during the 1992 presidential campaign was unique; candidates
utilized a variety of unconventional media outlets, including daytime talk shows
(e.g., Donahue), infomercials, cable programs (e.g., Music Television), radio
talk shows, etc. As a relatively recent phenomenon, this new political media
usage has not been extensively studied.
Graber (1996) has described the use of "new" media in political campaigns as
empowering to voters by allowing them to actively chose, edit, and frame their
mediated political news and bypass professional journalistic routines. Diamond,
McKay, and Silverman confirm how "Clinton and Perot consistently tried to go
'over the heads of the professionals' -- the journalists from the old-news
formats -- to reach 'the real people'" (1993, p. 259). The candidates,
furthermore, appear to have adopted a new delivery style (e.g., more casual and
self-deprecating) to suit these new media formats (Diamond, McKay, & Silverman,
1993).
In a study correlating exposure to news media with levels of cynicism among
Hong Kong residents, Wilkins asserts "that women both use the mass media
differently and hold distinct sets of political attitudes from men" (1995, p.
257). According to Wilkins (1995), media perpetuate a pattern of silencing
women's voices by legitimating and reinforcing patriarchal social and political
structures; women, therefore, seek different forms of media for different uses
than men.[1] This study hypothesizes that new forms of mediated political
discourse which by-pass traditional journalistic coverage will have a greater
appeal to women than men by rupturing some of these patriarchal restrictions.
By examining self-reported media use by feminist and non-feminists, Lull,
Mulac, and Rosen (1983) discovered that attitudes toward feminism predict
quantitative and qualitative differences in electronic media use. The authors
found that "the feminist personality attribute operates independent of sex" and
that sex may be increasingly "less predictive of media consumption" (Lull,
Mulac, & Rosen, 1983, p. 176). Through the use of a gender scale, the current
research similarly will examine gendered patterns of media use to obtain
political information.
In a survey during the 1990 congressional campaigns, Weaver and Drew (1993)
identified respondents' attention to the more unconventional formats of
television campaign advertisements, regional newspapers, and radio news shows
(rather than traditional television news programs and prestige newspapers) as
significant predictors of their knowledge of campaign issues. In two 1992
surveys, McLeod, Guo, Daily, Steele, Huang, Horowitz, and Chen (1996) examined
traditional and non-traditional media use by voters and found that women were
more likely to use non-traditional media outlets (e.g., political advertisements
and polls). The authors also found that use of a non-traditional medium
correlated to the utilization of other unconventional media outlets (McLeod, et
al., 1996). The current study also predicts that women will prefer
non-traditional media sources of political information more than men.
Chaffee, Zhao, & Leshner (1994) examined the use of MTV, talk shows, and late
shows as well as more conventional media sources by voters in the 1992
presidential election. Findings indicated that viewing candidates on talk shows
correlated with high candidate-issue knowledge, whereas, MTV viewing
corresponded to low candidate-issue knowledge (the correlation of late shows and
issue-knowledge was not significant) (Chaffee, Zhao, & Leshner, 1994). Women
were found to be less knowledgeable about campaign party and candidate issues
than men (Chaffee, Zhao, & Leshner, 1994).
One of the difficulties of studying voter usage of unconventional media sources
concerns the potential access and extensive use of those media to the majority
of survey respondents included in the study's sample (Mayer, 1994). In order to
avoid this problem, the current study will ask respondents about their likely
use of new media to obtain political information rather than measuring their
reported behaviors.
Based on the previous literature concerning the political gender gap and uses
of unconventional media during election campaigns, this study poses the
following hypotheses:
Hypothesis 1: The more "feminine" the respondent rates on a gender
scale, the more likely s/he will support sociotropic election issues,
identify with a Democratic Party affiliation, and express a
preference
to vote for Democratic candidates.
Hypothesis 2: The more "masculine" the respondent rates on a gender
scale, the more likely s/he will support egocentric election issues,
identify with a Republican Party affiliation, and express a
preference
to vote for Republican candidates.
The first two hypotheses are based on numerous research studies since 1980 that
have demonstrated a political gender gap between women and men, where women are
more likely to vote for the democratic candidate and favor political issues that
generally promote the social welfare (e.g., sociotropic) over personal concerns
(e.g., egocentric) (Abzug, 1984; Baxter & Lansing, 1983; Welch & Hibbing, 1992).
For the purposes of this study, the terms sociotropic and egocentric have been
expanded from Welch and Hibbing's (1992) original definitions to include a
broader range of political issues that previous studies have correlated to
women's (e.g., non-violent and nurturing) and men's (e.g., protective and
hawkish) voting patterns over the past 25 years (Abraham, 1995; Abzug, 1984;
Baxter & Lansing, 1983; Fitzpatrick, 1995; Huddy & Terkildsen, 1993; Kelber,
1994; Mandel, 1995; Mueller, 1991; Somma, 1992).
In an effort to extend the conventional research methodologies used in gender
gap analyses, this study will also measure gender rather than biological sex
differences between men and women. Adapted from the psychological literature, a
gender scale has been developed to measure respondents' identification with
personality traits culturally attributed to masculine and feminine categories
(Bem, 1984; de Bruyn, 1995; Diamond & Harstock, 1981; Hitchon & Chang, 1995;
Huddy & Terkildsen, 1993; Somma, 1992; Welch & Hibbing, 1992).
Two additional hypotheses will also be examined in this study:
Hypothesis 3: The more "feminine" the respondent rates on a gender
scale, the more likely s/he will utilize unconventional media as
sources for political information.
Hypothesis 4: The more "masculine" the respondent rates on a gender
scale, the more likely s/he will utilize conventional media as
sources
for political information.
The third and fourth hypotheses are based on previous research that has
identified distinct differences in media choices between women and men or
feminists and non-feminists (Lull, Mulac, & Rosen, 1983; Wilkins, 1995). Other
studies have specifically demonstrated a higher likelihood for women to use
unconventional political media sources (e.g., polls, advertisements) than men
(Chaffee, Zhao, & Leshner, 1994; McLeod, et al., 1996). The same gender scale
developed for the first two hypotheses will be tested to predict conventional
and unconventional media use by feminine and masculine survey respondents. For
all four hypotheses tests, gender scale results will be compared to the
biological sex of respondents.
Method
In order to test the study's hypotheses that 1) more feminine individuals are
likely to support the Democratic party, Democratic candidates, and sociotropic
political issues, 2) more masculine individuals are likely to support the
Republican party, Republican candidates, and egocentric political issues, 3)
more feminine individuals are likely to use unconventional political media
sources, and 4) more masculine individuals are likely to use conventional media
political sources, a telephone survey was developed.
Survey Design
The survey questions designed for this analysis were combined into a larger
survey project conducted by eight graduate students at the S. I. Newhouse School
of Public Communications at Syracuse University over a two-week period in
September and October of 1996. The entire survey instrument contained 120
questions covering various media-related research topics. A total of
twenty-eight questions were included on the survey specifically to test the four
hypotheses developed for this study. These questions predominately consisted of
Likert-type scales.
For the first two hypotheses, a series of questions were developed to measure
respondents' identification with sociotropic (e.g., non-violent, nurturing,
concerned with social welfare) versus egocentric (e.g., protective, hawkish,
related to individualistic concerns) political issues. Respondents were asked
to indicate agreement with six statements on a five-point, Likert-type scale
ranging from strongly agree to strongly disagree. Sociotropic issues included
protecting the environment, helping the homeless, and improving the quality of
education while egocentric issues included increasing defense spending, fighting
crime, and enlarging law enforcement forces. All of these issues have been
identified and tested in previous gender gap research (Abraham, 1995; Abzug,
1984; Baxter & Lansing, 1983; Fitzpatrick, 1995; Huddy & Terkildsen, 1993;
Kelber, 1994; Mandel, 1995; Mueller, 1991; Somma, 1992). Two questions asked
respondents to indicate their party affiliation and whether they were more
likely to vote for Democratic or Republican political candidates.
The gender scale used in all four hypotheses consisted of eight adjectives that
described specific personality traits that have been identified as masculine
(e.g., aggressive, assertive, ambitious, and strong) or feminine (cooperative,
nurturing, sensitive, and gentle) in previous research (Bem, 1984; de Bruyn,
1995; Diamond & Harstock, 1981; Hitchon & Chang, 1995; Huddy & Terkildsen, 1993;
Somma, 1992; Welch & Hibbing, 1992). Respondents were again asked to indicate
their agreement on the same five-point Likert-type scale with statements
describing themselves in terms of each personality trait (e.g., "The word
aggressive describes me").
For the third and fourth hypotheses, conventional and unconventional media use
were measured by asking respondents how likely they would be to obtain political
information from ten media sources: television news, newspapers, news magazines,
National Public Radio programs, live televised debates, Cable News Network
programs, tabloid television news, late night talk shows, radio call-in shows,
and the Internet/World Wide Web. The first five sources listed here were
considered conventional based on previous research, as well as their historical
status as traditional sources for political information; the last five sources
represent relatively new media formats for political information (Chaffee, Zhao,
& Leshner, 1994; McLeod, et al., 1996) and are considered non-conventional
political sources in this analysis.
Following a pre-test of the preliminary questionnaire, the survey instrument
was revised. Many questions were eliminated or re-written in order to address
problems identified from pre-test results. In addition, question order and
placement within the questionnaire were modified in order to refine the
instrument. Additional demographic questions were also included on the survey
instrument and used in this analysis.
Sampling
In order to generate a random sample of Syracuse, New York, residents, a CD-ROM
telephone directory (SelectPhone, Northeast, 1997, first quarter) was used to
develop the sampling frame for the study. All telephone numbers within the
local calling area of Syracuse University were initially selected from the
CD-ROM database. After eliminating all business and duplicate telephone
numbers, a list of 197,000 residential Syracuse telephone numbers was identified
for the study's sampling frame.
These telephone numbers were then randomly ordered based on a computer
generated list of random numbers and divided into groups of fifty telephone
numbers to create 23 replicates of 50 numbers each for a total of 1,150
telephone numbers for the study. Further randomization within each household
was achieved through the use of the Kish method, which was used to randomly
identify individual male and female members of the household to be included in
the study.
Interviewer Training
A total of 44 graduate students at Syracuse University were trained as
interviewers for the survey. All interviewers were trained by survey
supervisors prior to working in the field; they also received a comprehensive
training manual detailing proper interview procedures.
During data collection, interviewers attempted a second telephone call to
convert all respondents who initially refused to be interviewed. Survey
supervisors also verified ten percent of completed questionnaires by contacting
these respondents again to confirm the interviews had been conducted.
Following completion of the data collection, supervisors coded the
questionnaires for data entry. The statistical package SPSS Version 6.1 was
utilized for statistical data analysis. Frequency distributions, cross
tabulations, independent t-tests, analyses of variance, and Pearson correlation
coefficients were used for statistical analysis of the data.
Results
The final sample included a total of 413 questionnaires and yielded a
procedural response rate of 79%. Compared to U. S. Census data for the Syracuse
area, the survey's sample over-represented women and slightly under-represented
respondents with lower income and education levels. Table 4 provides
percentages for demographic data: Respondents were 58.7% women, 93.7%
Caucasian, with mostly high school (22.5%), some college (21.3%), or college
graduate (21.5%) levels of education. The most frequently occurring income
intervals were between the $20,000 to $50,000 ranges. Table 2 identifies the
mean age of respondents as 46.1 years.
Table 1 provides mean and standard deviations for the political issue
variables. Responses clustered around neutral (slightly leaning toward agree)
for most of the political issues (e.g., crime as the number one problem,
increasing the number of police officers, protecting the environment, and
helping the homeless). Overall, respondents tended to agree with spending more
to improve education and disagree that the U. S. should increase defense
spending.
For almost all of the personality traits listed in Table 2, most respondents
agreed that the traits described them. The word aggressive was the exception,
however, with responses aggregating around the neutral category. The aggressive
attribute also generated the highest standard deviation of any of the
personality traits.
As shown in Table 3, the use of the media for political information
demonstrated a wider range of responses. Survey results demonstrate that
respondents tended to be somewhat likely to read an election story in a
newspaper, watch live televised debates, or watch an election story on a
television news program or Cable News Network. Respondents were somewhat
unlikely to access the Internet, watch late night talk shows, listen to radio
call-in shows, or watch tabloid television programs to obtain political
information. Reading news magazines and listening to National Public Radio
programs received neutral responses.
Table 4 presents percentages for political affiliation data. The majority of
respondents identified with either the Republican (41.1%) or Democratic (33.9%)
parties, while 20.7% claimed to be independents and 4.3% identified another
political affiliation. Almost equal percentages would chose a Republican
(40.7%) or Democratic (39.6%) candidate if they had to vote purely for a
candidate's political party affiliation.
In order to develop a gender scale for the personality trait variables, a
varimax rotated factor analysis was performed. Results in Table 5 show two
factor loadings: The factor feminine includes the variables gentle, sensitive,
nurturing, and cooperative and the factor masculine includes the variables
assertive, aggressive, ambitious, and strong. An additive scale of the feminine
factors yielded a Cronbach's standardized item alpha of .73; a similar masculine
scale generated a standardized item alpha of .64. Creating masculine and
feminine scales by applying the corresponding weight from factor analysis
results did not improve reliability analyses. These factor analysis loadings
support the masculine and feminine traits identified in previous research (Bem,
1984; Diamond & Harstock, 1981; Hitchon & Chang, 1995; Huddy & Terkildsen, 1993;
Somma, 1992; Welch & Hibbing, 1992).
Crosstabulation results in Table 6 show that more males identify with the
Republican (43.6%) than Democratic (29.5%) party. The difference between
females party identification was much closer (e.g., a 1.9% difference between
Republican and Democratic affiliations). The chi square statistic, however,
indicates that these results were not significant. Significant results were
achieved for the choice between candidates solely along party lines: 42.4% of
males would choose Republican candidates while 44.0% of women would choose
Democratic candidates. Far fewer men would choose the Democratic candidate
(32.6%) compared to the women who would choose the Republican candidate (39.6%).
The independent t-tests in Table 7 demonstrate differences between male and
female respondents on various political issues. Women tended to have stronger
agreement that there should be more police officers on the streets, that the
government should spend more to help the homeless, and that more money should be
spent on education. The other three political issue (increasing defense
spending, crime as the number one problem, and protecting endangered wildlife)
did not generate statistically significant differences between men and women.
In Table 8, independent t-tests of the personality traits by sex demonstrated
that women were more likely than men to describe themselves as ambitious,
strong, cooperative, nurturing, sensitive, and gentle. The terms aggressive and
assertive did not generate statistically significant differences between male
and female respondents.
Only two of the eight media use variables in Table 9 demonstrated statistically
significant differences between men and women. Independent t-tests identify
females as somewhat more likely to watch live televised political debates and
election stories on tabloid television news programs than males.
Tables 10 and 11 contain one-way analyses of variance to test the study's first
and second hypotheses. Results indicate no significant differences between
political party identification or political party preference and ranking on the
feminine or masculine gender scales. These results show no support for these
two hypotheses. The crosstabulation results in Table 6 create an interesting
comparison. Based on biological sex rather than gender, females are more likely
than males to chose the Democratic candidate, while males are more likely than
females to chose the Republican candidate.
The Pearson correlation coefficients in Table 12 provide the final tests for
the first two hypotheses. In comparing feminine and masculine respondents and
their views on sociotropic political issues (e.g., protecting endangered
wildlife, helping the homeless, and improving the quality of education), two
significant correlations developed. First, the feminine scale was positively
correlated with spending more to help the homeless (as predicted by the study's
first hypothesis). Second, the masculine scale was positively correlated with
improving the quality of education (contrary to the first hypothesis).
For the egocentric political issues listed in Table 12 (e.g., increased
defense spending, crime as the number one problem, and the need for more police
officers), only one significant correlation emerged with the gender scales: The
more feminine the respondent, the greater agreement that there should be more
police officers on the streets. This finding did not support the study's second
hypothesis that predicted correlations between the masculine gender scale and
egocentric political issues.
Again a comparison of the gender scale results in Table 12 with the biological
sex findings in Table 7 proves interesting. For both analyses, female/feminine
respondents tended to agree with increasing the number of police officers and
spending more to help the homeless. The issue of improving the quality of
education, however, generated opposite results: More women agreed with this
issue and only the masculine scale generated a significant positive correlation.
In Table 12, the two gender scales are positively correlated; since the
femininity and masculinity scales are not mutually exclusive categories, this
positive correlation is possible. The independent t-tests for personality
traits and biological sex in Table 8 reveal that women are more likely to agree
with almost all of the personality traits, which may help to explain this
positive correlation between gender scales.
The correlations in Table 13 test the study's final two hypotheses regarding
political media sources and gender scale attributes. Four significant
correlations emerged: The feminine scale was positively correlated with
television news and the Internet, while the masculine scale was positively
correlated with Cable News Network programs and the Internet. These findings
did not support the third and fourth hypotheses. The biological sex and media
source t-tests in Table 9 indicate differences between live televised debates
and tabloid television programs (which did not significantly correlate on gender
scale results).
Discussion
The fact that this study's results failed to replicate previous political
gender gap findings is significant. This study demonstrates that the historical
distinction between traditionally "male" and "female" political issues may be
changing in today's political climate. This analysis also successfully
developed a reliable gender scale which extends conventional telephone survey
research methodology.
Table 6 shows limited support for the political party gender gap between women
and men identified in previous studies (Abraham, 1995; Abzug, 1984; Baxter &
Lansing, 1983; Fitzpatrick, 1995; Huddy & Terkildsen, 1993; Kelber, 1994;
Mandel, 1995; Mueller, 1991; Somma, 1992) continues to exist today. Women were
more likely than men to chose a Democratic candidate than a Republican one.
The differences between women and men along social welfare (e.g., sociotropic)
and personal (e.g., egocentric) political issues identified from previous
research did not receive clear support in the current study. Table 7
demonstrates that women did show stronger agreement than men on certain
environmental and social welfare concerns (e.g., protecting endangered wildlife
and helping the homeless). Women, however, also supported a "protective" and
"hawkish" stand traditionally attributed to men (e.g., increasing the number of
police officers) (Abraham, 1995; Abzug, 1984; Baxter & Lansing, 1983;
Fitzpatrick, 1995; Huddy & Terkildsen, 1993; Kelber, 1994; Mandel, 1995;
Mueller, 1991; Somma, 1992; and Welch & Hibbing, 1992). Due to heightened
levels of crime in the United States over the past 25 years, women may be
identifying personal safety as an increasingly important political issue.
Pearson correlations in Table 12 provide insight for future research on gender
gap political issues. The three egocentric issues were positively correlated
with each other, as were the three sociotropic issues. The negative
correlations one would expect between egocentric and sociotropic issues,
however, did not emerge (except for increasing defense spending and spending
more to help the homeless). In fact, two egocentric issues (e.g., fighting
crime and increasing the number of police officers) were positively correlated
with most of the sociotropic issues. Future research in this area may conclude
that these "traditional" political issues separating men and women may no longer
be appropriate categories.
This study also provided one of the first attempts at developing a gender scale
for telephone survey research. Factor analysis results in Table 5 demonstrate
that the eight personality traits measured for the scale clearly load on two
distinct factors. Although Table 8 demonstrates significant differences between
men and women for the majority of personality traits measured, women tended to
agree with almost all of the traits more than men. Future research in this area
should generate methodological analyses for further gender scale development:
The influence of social desirability on personality trait responses and the
nature of the non-exclusive categorizations of masculine and feminine should be
examined.
The results from this study, finally, are informative for future research on
conventional and unconventional political media sources. The first five
variables listed in Table 13 were identified as "conventional" media sources and
were all positively correlated with one another. Of the final five
"unconventional" media sources, however, only three positive correlations
occurred (e.g., tabloid television news with Cable News Network programs, late
night talk shows, and the Internet). All of the conventional sources positively
correlated with Cable News Network programs. Call-in radio programs and the
Internet also correlated positively with four and three, respectively, of the
five unconventional media sources. These findings provide heuristic
associations between the use of various political media sources and how they
relate to each other.
Table 1. Means and standard deviations for political issue variables.
Variables * Mean Std. Deviation N
________________________________________________________________________
More money should be spent to
improve the quality of education
in the United States. 4.13 1.04 412
It is important for the government
to help protect endangered wildlife
like the spotted owl. 3.78 0.97 412
Crime is the number one
problem facing our country. 3.65 1.13 412
There should be more police
officers on the streets in
our country. 3.62 0.96 411
The government should spend
more to help the homeless. 3.60 1.02 411
The United States must
increase defense spending. 2.82 1.07 403
* Responses were coded: 5 = strongly agree, 4 = agree, 3 = neutral, 2 =
disagree, 1 = strongly disagree.
Table 2. Means and standard deviations for personality trait and age
variables.
Variables Mean Std. Deviation N
________________________________________________________________________
The word cooperative describes
me.* 4.23 0.64 398
The word sensitive describes
me.* 4.18 0.75 398
The word nurturing describes
me.* 4.02 0.79 392
The word gentle describes
me.* 3.98 0.73 396
The word strong describes
me.* 3.94 0.78 398
The word ambitious describes
me.* 3.94 0.81 395
The word assertive describes
me.* 3.80 0.90 394
The word aggressive describes
me.* 3.22 1.12 397
_____________
Age (in years) 46.1 16.1 392
* Responses were coded: 5 = strongly agree, 4 = agree, 3 = neutral, 2 =
disagree, 1 = strongly disagree.
Table 3. Means and standard deviations for media use variables.
Variables * Mean Std. Deviation N
________________________________________________________________________
How likely would you be to
read a story about the election
in newspapers? 3.97 1.33 407
How likely would you be to
watch live televised debates? 3.70 1.45 404
How likely would you be to
watch a story about the election
on a television news program? 3.56 1.36 406
How likely would you be to watch
a story about the election on CNN
-- Cable News Network? 3.43 1.55 401
How likely would you be to
read a story about the election
in news magazines like Time? 2.93 1.57 406
How likely would you be to
listen to campaign discussions
on National Public Radio
programs? 2.66 1.60 403
How likely would you be to
watch a story about the election
on tabloid TV programs
like A Current Affair? 2.44 1.51 401
How likely would you be to
listen to campaign discussions
on radio call-in shows? 2.00 1.31 405
How likely would you be to watch
discussions about the election on
late night talk shows like David
Letterman? 1.77 1.28 406
Table 3 (continued). Means and standard deviations for media use variables.
Variables * Mean Std. Deviation N
________________________________________________________________________
How likely would you be to
find election information on the
Internet or World Wide Web? 1.75 1.32 400
* Responses were coded: 5 = very likely, 4 = somewhat likely, 3 = neutral, 2 =
somewhat unlikely, 1 = very unlikely.
Table 4. Percentages for political affiliation and demographic variables.
Variables %
________________________________________________________________________
Which political party do you most
closely identify with?
Republican 41.1
Democrat 33.9
No party or independent 20.7
Other . 4.3 .
100.0%
(N=372)
If you were voting and had to choose
between two candidates you knew nothing
about except their political party, would
you choose the Democrat or the Republican?
Democrat 39.6
Republican 40.7
Neither 18.0
Other . 1.7 .
100.0%
(N=356)
Sex
Female 58.7
Male 41.3 .
100.0%
(N=397)
Race
White 93.7
Black or African descent 3.6
Hispanic 0.8
Asian 1.0
Native American 0.5
Other . 0.6 .
100.0%
(N=394)
Education
3rd - 12th grade 10.9
High school diploma or GED 22.5
Some college 21.3
Associates degree 12.4
Bachelors degree 21.5
Graduate degree 11.4 .
100.0%
(N=395)
Table 4 (continued). Percentages for political affiliation and demographic
variables.
Variables %
________________________________________________________________________
Income
less than $10,000 6.2
$10,000 - $19,999 10.6
$20,000 - $29,999 14.4
$30,000 - $39,999 14.1
$40,000 - $49,999 15.8
$50,000 - $59,999 11.1
$60,000 - $69,999 7.3
$70,000 - $79,999 9.4
$80,000 or more 11.1 .
100.0%
(N=341)
Gender Gap
Table 5. Major factor loadings (varimax rotated) for personality trait
variables.
Factor 1 Factor 2
Variables * Feminine Masculine
________________________________________________________________________
The word gentle
describes me. .81 -.04
The word sensitive
describes me. .78 -.04
The word nurturing
describes me. .77 .11
The word cooperative
describes me. .58 .18
The word assertive
describes me. .05 .80
The word aggressive
describes me. -.20 .74
The word ambitious
describes me. .12 .70
The word strong
describes me. .27 .52
___________________
Eigenvalue 2.44 1.87
Percent of variance accounted for 30.5% 23.4%
* Responses were coded: 5 = strongly agree, 4 = agree, 3 = neutral, 2 =
disagree, 1 = strongly disagree. Table 6. Crosstabulation of political
affiliation by respondent's sex.
Respondent's sex
Which political party do you most
closely identify with? Male Female
___________________________________________________________________
Republican 43.6 39.3
Democrat 29.5 37.4
No party or independent 21.8 19.9
Other 5.1 3.4
___________________________________________________________________
100.0% 100.0%
(N=156) (N=206)
X2 = 2.81, df = 3, ns
Cramer's V = .09
If you were voting and had to
choose between two candidates Respondent's sex
you knew nothing about except their
political party, would you choose
the Democrat or the Republican? Male Female
___________________________________________________________________
Democrat 32.6 44.0
Republican 42.4 39.6
Neither/Other* 25.0 16.4
___________________________________________________________________
100.0% 100.0%
(N=144) (N=207)
X2 = 6.06, df = 2, p < .05
Cramer's V = .13
* In order to reduce crosstabulation results so that less than 20 percent of
cells contained expected frequencies of less than five, the neither and other
categories were collapsed into one group. Table 7. Independent t-tests for
political issue variables by sex.
Respondent's sex
Male Female
Means Means
Variables (& SD) (& SD) t value df significance
________________________________________________________________________
The United States must 2.87 2.74
increase defense spending.* (1.08) (1.06) 1.17 385 ns
Crime is the number one 3.56 3.72
problem facing our country.* (1.14) (1.11) -1.38 394 ns
There should be more police
officers on the streets in 3.41 3.75
our country.* (0.99) (0.92) -3.46 336 p < .001
It is important for the
government to help protect
endangered wildlife like the 3.75 3.81
spotted owl.* (1.04) (0.92) -0.64 324 ns
The government should
spend more to help 3.36 3.74
the homeless.* (1.03) (0.98) -3.68 337 p < .001
More money should be
spent to improve the
quality of education in 3.98 4.24
the United States.* (1.11) (0.97) -2.48 395 p < .013
* Responses were coded: 5 = strongly agree, 4 = agree, 3 = neutral, 2 =
disagree, 1 = strongly disagree.
Table 8. Independent t-tests for personality trait variables by sex.
Respondent's sex
Male Female
Means Means
Variables (& SD) (& SD) t value df significance
________________________________________________________________________
The word aggressive 3.30 3.17
describes me.* (1.05) (1.17) 1.18 371 ns
The word assertive 3.76 3.83
describes me.* (0.82) (0.95) -0.76 391 ns
The word ambitious 3.84 4.02
describes me.* (0.77) (0.82) -2.22 392 p < .05
The word strong 3.81 4.03
describes me.* (0.72) (0.81) -2.78 395 p < .01
The word cooperative 4.11 4.31
describes me.* (0.66) (0.62) -3.05 339 p < .01
The word nurturing 3.64 4.29
describes me.* (0.80) (0.68) -8.28 306 p < .001
The word sensitive 3.95 4.34
describes me.* (0.75) (0.70) -5.28 335 p < .001
The word gentle 3.79 4.12
describes me.* (0.72) (0.72) -4.58 393 p < .001
* Responses were coded: 5 = strongly agree, 4 = agree, 3 = neutral, 2 =
disagree, 1 = strongly disagree.
Table 9. Independent t-tests for media use variables by sex.
Respondent's sex
Male Female
Means Means
Variables (& SD) (& SD) t value df significance
________________________________________________________________________
How likely would you be
to watch a story about the
election on a television 3.45 3.69
news program?* (1.34) (1.33) -1.71 394 ns
How likely would you be
to read a story about the 3.90 4.07
election in newspapers?* (1.28) (1.31) -1.31 394 ns
How likely would you be
to read a story about the
election in news magazines 2.79 3.04
like Time?* (1.47) (1.61) -1.58 368 ns
How likely would you be
to listen to campaign
discussions on National 2.81 2.57
Public Radio programs?* (1.56) (1.61) 1.44 390 ns
How likely would you be
to watch live televised 3.52 3.86
debates?* (1.47) (1.39) -2.34 333 p < .05
How likely would you be
to watch a story about the
election on CNN -- 3.38 3.49
Cable News Network?* (1.51) (1.56) -0.70 389 ns
How likely would you
be to watch a story about
the election on tabloid
TV programs like A 2.24 2.62
Current Affair?* (1.32) (1.62) -2.55 381 p < .011
Table 9 (continued). Independent t-tests for media use variables by sex.
Respondent's sex
Male Female
Means Means
Variables (& SD) (& SD) t value df significance
________________________________________________________________________
How likely would you be
to watch discussions about
the election on late night
talk shows like David 1.70 1.82
Letterman?* (1.15) (1.35) -0.95 378 ns
How likely would you be
to listen to campaign
discussions on radio 2.06 1.98
call-in shows?* (1.28) (1.34) 0.62 392 ns
How likely would you be
to find election information
on the Internet or World 1.65 1.80
Wide Web?* (1.22) (1.37) -1.15 368 ns
* Responses were coded: 5 = very likely, 4 = somewhat likely, 3 = neutral, 2 =
somewhat unlikely, 1 = very unlikely.
Table 10. One-way analyses of variance for feminine scale and political party
identification; and masculine scale and political party identification.
Political party identification
Variable Republican Democrat None/Indep. F df sig.
Mean Mean Mean
(SD) (SD) (SD)
________________________________________________________________________________
_________
Feminine Scale* 16.32 16.80 16.13
(2.16) (2.15) (2.29) 2.58 340 ns
____________________________
Masculine Scale** 14.99 15.17 14.64
(2.39) (2.65) (2.43) 1.02 341 ns
*The feminine scale is an additive scale containing the following personality
trait variables: gentle, sensitive, nurturing, and cooperative. Cronbach's
reliability analysis yielded a standardized item alpha of .73. Each personality
trait variable was originally coded as: 5 = strongly agree, 4 = agree, 3 =
neutral, 2 = disagree, 1 = strongly disagree.
**The masculine scale is an additive scale containing the following personality
trait variables: assertive, aggressive, ambitious, and strong. Cronbach's
reliability analysis yielded a standardized item alpha of .64. Each personality
trait variable was originally coded as: 5 = strongly agree, 4 = agree, 3 =
neutral, 2 = disagree, 1 = strongly disagree.
Table 11. One-way analyses of variance for feminine scale and political
candidate preference; and masculine scale and political candidate preference.
Political candidate preference
Variable Democrat Republican None/Indep. F df sig.
Mean Mean Mean
(SD) (SD) (SD)
________________________________________________________________________________
_________
Feminine Scale* 16.60 16.40 16.56
(2.22) (2.16) (2.16) 0.33 337 ns
____________________________
Masculine Scale** 15.15 14.76 14.90
(2.57) (2.49) (2.59) 0.84 340 ns
*The feminine scale is an additive scale containing the following personality
trait variables: gentle, sensitive, nurturing, and cooperative. Cronbach's
reliability analysis yielded a standardized item alpha of .73. Each personality
trait variable was originally coded as: 5 = strongly agree, 4 = agree, 3 =
neutral, 2 = disagree, 1 = strongly disagree.
**The masculine scale is an additive scale containing the following personality
trait variables: assertive, aggressive, ambitious, and strong. Cronbach's
reliability analysis yielded a standardized item alpha of .64. Each personality
trait variable was originally coded as: 5 = strongly agree, 4 = agree, 3 =
neutral, 2 = disagree, 1 = strongly disagree.
Table 12. Pearson correlation coefficients for political issues and gender
scale variables.
Variables 2. 3. 4. 5. 6. 7. 8.
______________________________________________________________________
1. Increase
defense .15 b .20 c -.03 -.13 b -.05 -.00 .00
spending * (402) (401) (402) (401) (402) (380) (382)
2. Crime as
number one ___ .33 c .06 .25 c .15 b .06 .04
problem * (410) (411) (410) (411) (389) (390)
3. More police ____ .14 b .28 c .25 c .19 c .04
officers on streets * (410) (409) (410) (389) (390)
4. Protect endangered ____ .36 c .31 c .05 -.04
wildlife * (410) (411) (390) (390)
5. Spend more to help ____ .39 c .12 a .01
the homeless * (410) (388) (389)
6. Improve the quality _____ .09 .15 b
of education * (389) (390)
7. Feminine Scale ** _____ .11 a
(386)
8. Masculine Scale *** _____
___________________________________
* Responses were coded: 5 = strongly agree, 4 = agree, 3 = neutral, 2 =
disagree, 1 = strongly disagree.
** The feminine scale is an additive scale containing the following personality
trait variables: gentle, sensitive, nurturing, and cooperative. Cronbach's
reliability analysis yielded a standardized item alpha of .73. Each personality
trait variable was originally coded as: 5 = strongly agree, 4 = agree, 3 =
neutral, 2 = disagree, 1 = strongly disagree.
***The masculine scale is an additive scale containing the following personality
trait variables: assertive, aggressive, ambitious, and strong. Cronbach's
reliability analysis yielded a standardized item alpha of .64. Each personality
trait variable was originally coded as: 5 = strongly agree, 4 = agree, 3 =
neutral, 2 = disagree, 1 = strongly disagree.
___________________________________
a p < .05
b p < .01
c p < .001
Table 13. Pearson correlation coefficients for political media use and gender
scale variables.
Variables 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
________________________________________________________________________________
_______________
1. Television .20 c .16 b .10 a .48 c .35 c .19 c .07 .05 .03 .11 a .02
News * (406) (405) (402) (403) (400) (400) (405) (404) (399) (389) (390)
2. Newspapers * ___ .29 c .13 b .26 c .21 c .07 .04 .14 b .09 .06 .02
(406) (403) (404) (401) (401) (406) (405) (400) (389) (390)
3. News ____ .28 c .21 c .28 c -.02 .01 .11 a .17 c .01 .07
magazines * (402) (403) (401) (400) (405) (404) (399) (388) (389)
4. National Public ____ .26 c .17 c -.18 c -.05 .36 c .12 a .04 .07
Radio programs* (401) (397) (397) (402) (402) (397) (386) (387)
5. Live televised ____ .36 c .06 .05 .16 c .12 a .06 .06
debates * (399) (399) (403) (402) (398) (387) (388)
6. Cable News _____ .13 b .03 .07 .07 .02 .19 c
Network programs * (396) (400) (399) (395) (384) (385)
7. Tabloid television _____ .21 c .05 .11 a .01 -.02
programs * (400) (400) (398) (384) (385)
8. Late night _____ -.03 .05 .00 .07
talk shows * (404) (399) (388) (389)
9. Call-in radio _____ .09 -.02 .04
programs * (400) (387) (388)
10. Internet/World _____ .10 a .11 a
Wide Web * (383) (384)
11. Feminine Scale ** _____ .11 a
(386)
12. Masculine Scale *** _____
Table 13 (continued). Pearson correlation coefficients for political media use
and gender scale variables.
___________________________________
* Responses were coded: 5 = very likely, 4 = somewhat likely, 3 = neutral, 2 =
somewhat unlikely, 1 = very unlikely.
** The feminine scale is an additive scale containing the following personality
trait variables: gentle, sensitive, nurturing, and cooperative. Cronbach's
reliability analysis yielded a standardized item alpha of .73. Each personality
trait variable was originally coded as: 5 = strongly agree, 4 = agree, 3 =
neutral, 2 = disagree, 1 = strongly disagree.
***The masculine scale is an additive scale containing the following personality
trait variables: assertive, aggressive, ambitious, and strong. Cronbach's
reliability analysis yielded a standardized item alpha of .64. Each personality
trait variable was originally coded as: 5 = strongly agree, 4 = agree, 3 =
neutral, 2 = disagree, 1 = strongly disagree.
___________________________________
a p < .05
b p < .01
c p < .001
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[1] The work of Tuchman (1978), Gitlin (1980), and van Zoonen (1994)
also discuss the media's role in perpetrating the dominant ideology of
the ruling class.
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