Sex-Linked Trait Indexes Among Baby-Boomers and Pre-Boomers: a Research Note

ABSTRACT - This paper presents an examination of sex traits in two female age cohorts: Baby-Boomers and Pre-Boomers. Relationships between variables and trait indexes past research considered sex-linked were assessed. Findings indicate that the past interpretations of femininity still hold true. However, current perception of masculinity traits seems socially redefined to self-assurance and to incorporate femininity as well, which may explain much contradiction in prior sex research. Indications are that the two cohorts do interpret sex role traits differently.


Benny Barak and Barbara Stern (1986) ,"Sex-Linked Trait Indexes Among Baby-Boomers and Pre-Boomers: a Research Note", in NA - Advances in Consumer Research Volume 13, eds. Richard J. Lutz, Provo, UT : Association for Consumer Research, Pages: 204-209.

Advances in Consumer Research Volume 13, 1986      Pages 204-209


Benny Barak, Hofstra University

Barbara Stern, Kean College of New Jersey


This paper presents an examination of sex traits in two female age cohorts: Baby-Boomers and Pre-Boomers. Relationships between variables and trait indexes past research considered sex-linked were assessed. Findings indicate that the past interpretations of femininity still hold true. However, current perception of masculinity traits seems socially redefined to self-assurance and to incorporate femininity as well, which may explain much contradiction in prior sex research. Indications are that the two cohorts do interpret sex role traits differently.


The relationship of sex traits, sex roles and sex-linked characteristics has long been of interest in multidisciplinary research. Within the past decade, these topics have surfaced in marketing literature; while the relationship of sexual identity and consumer behavior has been investigated to some extent, much more remains to be discovered. This paper presents a reexamination of sex traits in an age-related social context.

Sex traits are treated in two ways: one, as simple unidimensional self-descriptions--either "feminine" or "masculine"; two, as multi-trait indexes of self-linked identity--FEMININITY or MASCULINITY.

The currently accepted sex role categories of Feminine, Masculine, and Androgynous, all based on combinations of these FEMININITY and MASCULINITY trait indexes (Bem 1974), have not been especially useful to consumer behaviorists. We felt that a reexamination of the uncombined indexes might provide more practical results than the combined typology has done so far. Additionally, since the central changes in society concerning appropriate role stereotyping have occurred since World War II, and have mainly impacted on the roles of women, we also felt that concepts of FEMININITY and MASCULINITY might very well be associated with the dimensions of age in women consumers.

We thus decided to conduct an exploratory study to examine the way selected demographic, psychographic, and behavioral variables relate to self-perceived sex traits in two female age cohorts: Baby-Boomers (25-39) and Pre-Boomers (40-64).

Sex Role Research

Pre-1970's sex role research assumed that "healthy" individuals adopted the sex role appropriate to their gender, and demonstrated only those traits judged desirable for that gender by society (Robinson and Green 1981). Traditional sex role theories, however, were unable to accommodate the dynamic changes in America's cultural milieu dating from the late 1960's (Bem 1974, 1975, 1977; Bem and Lenney 1976; Robinson and Green 1981). The shattering of cultural stereotypes in the wake of the women's liberation movement forced the conclusion that sex roles and biological Render are not necessarily the same.

Self-Perceived Sex Concepts

The theoretical framework for measuring combinations of feminine and masculine traits to determine sex role concepts is the Bem Sex Role Inventory (BSRI; Bem 1974). The BSRI is a self-descriptive survey instrument relying on a 7-point true-untrue scale to measure respondents' identification with 60 characteristic qualities. Independent panels of judges in the early 1970's established these attributes as either feminine, masculine, or non-gender related--for example, helpful or happy. Each of the BSRI role typologies is measured by 20 of the attributes; a respondent's identification with these qualities provides insight about his/her self-perception as feminine or masculine.

BSRI research has been used to assign individuals to four categories: Feminine, Androgynous, Masculine, and Undifferentiated. This categorization relies on various combinations of the femininity and masculinity scores, minus the non-gender subscale. Most of the BSRI based sex research (e.g., Bem 1974, 1977; Bem et al 1976; Robinson and Green 1981) is concerned with the Androgynous sex role--high scores in both femininity and masculinity--and its difference from the Feminine role--high femininity and low masculinity scores. Few differences have been found between Androgyny and either the Masculine--low femininity, and high masculinity--or Undifferentiated--low femininity and low masculinity--sex roles. Bem's widely used research has led to the reevaluation of femininity and masculinity as separate and blendable constructs, not bipolar opposites.

There has been growing marketing interest in the sexual revolution's impact on the American woman's interpretation of femininity and masculinity (e.g., Caffetera 1984; Kanter and Wortzel 1985; Kilbourne 1984). Some consumer studies have been done on product and brand usage (e.g., Allison et al. 1980; Gentry et al. 1978). Marketers have also examined sex roles and stereotypes on the mass media, with particular emphasis in advertising portrayals (Coughlin and O'Connor 1985). Past research emphasis, when the BSRI was employed, has been almost exclusively on combinations of traits, especially the Androgynous. Results, however, have been disappointing: the Androgynous role, like the 1960's Unisex one, seems to be a fad (Caffetera 1984).


We felt that a reexamination of the sex traits of femininity and masculinity in the light of a woman consumer's age might be especially useful. The role changes concerning education, employment, and sexuality seemed likely to affect the Baby-Boom woman differently from the Pre-Boomer woman. We thus conducted an exploratory study to investigate the way sex traits, measured by BSRI items, correlate with a number of variables in the two female populations.

Variables Selected

Multidisciplinary sex-role research has established sets of variables associated with self-perceived sexual roles measured in various ways. Contradictory evidence has characterized such research, perhaps caused in part by differences in sampling procedures and populations studied. Even when contradictory findings occur, however, certain variables often show significant relationship to sex traits. Tested relationships are listed in Tables 1 and 2;where male and female populations were analyzed separately, only female ones are shown.

In addition, one other hitherto untested potential correlate was also selected on the basis of logic: Opinion Leadership in grooming and cosmetic products.

Research Methodology

From 1982/84, a convenience sample of 698 women in the New York Metropolitan area completed a ten page, 30-45 minute self-report questionnaire. Marketing students trained in survey techniques distributed and collected the questionnaires. An age quota sampling procedure ensured a representative population of women 25 to 64, with a median age of 40. The total population sample was edited down to 280 Baby-Boomers (25-39) with a mean age of 31.25, and 334 Pre-Boomers (40-64) with a mean age of 50.88, who complete the BSRI. The questionnaire, used for other purposes as well, incorporated numerous variables.





Survey Instrument (Questionnaire)

Sex Traits. Four sex traits are employed in this study. Two of these are sex-linked trait indexes, FEMININITY and MASCULINITY, the dependent study variables. Varimax rotated factor analysis of feminine and masculine BSRI (Bem 1974) characteristics--a common technique in such research (e.g., Gaudreau 1977; Whetten and Swindells 1977)--led to the selection of items with a loading of .55 or higher for either a FEMININE or a MASCULINE trait index. Appendix A shows the 20 specific items identified by factor analysis as having sufficiently high loadings to be included in these indexes. Scoring relies on a simple summation of the ten factor-loaded feminine items for FEMININITY, and the ten masculine items for MASCULINITY. There are two additional sex-traits measured: self-ascribed "feminine" and "masculine," single items on the BSRI scale (factor loadings < .55), scored from 1 to 7 by the respondent.

Age Variables. Four age measures were selected. (1) Chronological age, measured directly in years; (2) Identity Age (Cutler 1982), measured by a respondent's self-perception as "young" (score=0) or "middle-aged" (score=1); (3) cognitive age (Barak and Gould 1985) measured by a respondent's assessment of personal age identity in terms of four age dimensions (Feel/Age, Look/Age, Do/ Age, and Interest/Age) expressed in years; and (4) Ideal Age (Barak and Gould 1985), measured by a respondent's answer to the question, "What do you consider to be a person's IDEAL age?" in years.

Demographics. Five demographic variables were selected. These were scaled dichotomously to avoid empty cells. (1) Education, scored in years; (2) Occupation scored as a dummy variable, with "professional" or "executive" = 1, all others = 0; (3) Employment outside the home also a dummy variable, "fully-employed" = 1, 'not fully employed" = 0; (4) Income, with personal income under $20,000 = 0, $20,000+ = 1; and (5) Health Status, measured by the question, "How would you describe the state of your health?" Scoring was "Excellent and Good" = 1, "So-So, Bad and Terrible" = 0.

Family Measures. Three variables concerning household and offspring were selected. (1) Marital Status, with "marrieds" = 1, "widowed, separated, divorced, and singles" = 0; (2) Household Size, based on the question,"How many persons are presently in your household, including yourself?" and (3) Number of Children, based on a straightforward question: "Bow many children do you have?" Both (2) and (3) were scored numerically

Psychographics. Each of the two scales employed, (1) Self-Confidence (Reynolds and Darden 1971) and (2) Morale (Barak and Gould 1985), is based on four Likert summation items to which respondents indicated agreement/disagreement. Responses were then factor analyzed to establish the specific AIO scales employed (see Wells 1975). A typical Self-Confidence scale statement is, "I think I have a lot of personal ability." Morale measures a condition of well-being, particularly happiness with one's age-status, as indicated by a statement such as "These are the best years of my life."

Social Traits. Three social traits were selected. (1) Perceived Risk (Error-Tolerance; Schiffman 1972) differentiates between respondents who, when shopping in a supermarket, prefer to try a new brand of product when it first comes out, and those who prefer to wait and learn how good a product is before trial. Perceived risk is thus a dummy variable: error-tolerants who try produces first = 1, others = 0. (2) Opinion Leadership (Katz and Lazersfeld 1955); another dummy measure was scored dichotomously, since the "not-sures" and non-opinion leaders are distinct from those who identify themselves as opinion leaders. This measure thus scores respondents who agree that "friends and neighbors often ask my advice about grooming and cosmetic products" = 1, all others = 0; (3) Risk Inclination scores respondents 1 to 7 according to their degree of self-perception as "willing to take risks."

Leisure Time Behaviors. Four leisure time variables were selected. Respondents are scored numerically in terms of their answers to "Row many times did you engage in the following activities in the last three months?" (1) Running, (2) Swimming, (3) Dancing, and (4) Going to a Bar.


We decided to investigate the following Propositions in both age cohorts:

Proposition I - All sex-related traits are significantly interrelated.

On the basis of variables assessed for relationship with sex roles/traits (see Tables 1 and 2), Propositions II and III were set forth:

Proposition II - Femininity will correlate negatively with: Chronological Age, Education, Employment Status, Occupation, Income, Health, Marital Status, Perceived Risk, and Risk Inclination. Femininity will correlate positively with: Number of Children, Self-Confidence and Morale. Femininity will not significantly correlate with Self-Perceived Age, Leisure Time Activities and Ideal Age.

Proposition III - Masculinity will correlate negatively with: Chronological Age, Self-Perceived Age, and Number of Children. Masculinity will correlate positively with: Education, Occupation, Employment Status, Income, Health, Marital Status, Self-Confidence, Morale, Perceived Risk, Risk Inclination, and Leisure Time Activities. Masculinity will not significantly correlate with Ideal Age.

On the basis of logical association with sex roles/traits, Proposition IV was set forth:

Proposition IV - Femininity will not correlate significantly, and Masculinity will correlate significantly with Opinion Leadership.

Since the relationship between sex traits and other consumer variables has not previously been considered in an age cohort context, the study also set out to compare and contrast relationships found in both age groups.


All statistical procedures relied on the Statistical Package for the Social Sciences (SPSS--Nie et al. 1975; Hull and Nie 1981). The first procedure, reliability tests, showed all multiple-item scales in the study to be sufficiently reliable: only measures with a coefficient ALPHA >.5 were included. The research flow model tested is shown in Figure 1.



Correlation and Regression Procedures

To assess the propositions, three separate stages of investigation took place. The first stage, testing Proposition I, used Pearson correlations between the four types of sex traits. The results of this intercorrelation are in Table 3.



Part of Proposition I must be rejected for the Baby-Boomer cohort: no significant relationship was established between MASCULINITY and self-ascribed "masculine." One surprising finding was that in the two cohorts the correlation between both FEMININITY and self-ascribed "feminine" visa-vis MASCULINITY was positive: we expected these relationships to work in opposite directions. All other relationships were in logical directions.

The second stage, testing Propositions II, III and IV, used Pearson and Bi-Serial (tummy variable) correlations between the two trait-indexes and the independent variables. The resulting correlates shown in Table 4 establish the independent variables for which Propositions II, III and IV were accepted.



The third stage, to confirm the Propositions and compare findings in both cohorts, used Forward Stepwise Regression. A total of eight multiple regressions were performed, four in each cohort. The collinearity index (Chapman and Staelin 1982) was <.05 for all eight functions.

Table 5 presents the FEMININITY functions in both cohorts, WITHOUT (Functions I and II), and then WITH sex traits (Functions III and IV). MASCULINITY functions are presented in the same order: WITHOUT (Functions V and VI) and WITH sex traits (Functions VII and VIII). Function VII was developed without self-ascribed "masculine," since that was not a Masculinity correlate.



Discussion of Results

Functions I and II show that when FEMININITY is developed without the sex traits, the variance explained is rather limited: R square = .08 for 1, and R Square = .09 for II. Furthermore, the variables in both Functions differ totally.

Functions III and IV show that when sex traits enter the regressions, the first step in both cohorts is "feminine ' and the second step, MASCULINITY. The variance explained in both cases increases nearly fourfold: R Square = .31 for III and R Square = .33 for IV. The other independent variables remain basically the same, except that Opinion Leadership drops out in the Baby-Boom cohort. The entry of "feminine" and MASCULINITY in III and IV shows that FEMININITY indeed measures a sex-related dimension. The strength of the relationship between "feminine" and FEMinINITY is shown by the relatively high correlation between the two, and first step entry. MASCULINITY also shows correlations of similar strength in both cohorts. Moreover III and IV show not only a significant relationship between FEMININITY and MASCULINITY--step 2 in both--but also a positive one.

Functions V and VI show that when MASCULINITY is developed without the sex traits, a fair amount of variance is explained: R Square = .45 for V, and R Square = .34 for VI. In both functions, Self-Confidence and Risk Inclination form the first steps. The fourth step is also similar, in each case a form of self-perceived age. The major difference between the functions is in step 3: in the Baby-Boomer cohort, Dancing, and in the Pre-Boomers, Professional and Executive status occupy this step.

Functions VII and VIII show that when sex traits enter the regressions, the first two steps are again Self-Confidence and Risk Inclination, which confirms these variables as the main determinants of the MASCULINITY trait index. The third step in both functions is FEMININITY, again a positive association. The entry of FEMININITY raises the variance explained in the Baby-Boom cohort: R Square = .51 for VII. The addition of sex traits in the Pre-Boomers also helps raise the variance explained: R Square = .39 for VIII. In VIII, both "masculine" and "feminine" enter, as steps 5 and 7. All three sex traits thus show a positive relationship. This implies that the MASCULINITY trait index is still slightly associated with the sex-linked masculine dimension in the minds of respondents 40+.


It is clear that when MASCULINITY is the dependent variable all of the independent variables (except Number of Children as step 6, Function VIII) reflect a form of SELF-ASSURANCE. The ten items that form this trait index (Appendix A) are all traits characteristic of a highly self-assured woman. We thus suspect that this trait index is NOT sex-linked as originally thought, but, rather, a NON-SEX related self-concept measure. These ten traits might have been considered stereotypically masculine in the early 1970's, but the sexual revolution seems to have wrought a shift in perception. We therefore suggest the reinterpretation of the MASCULINITY index as SELF-ASSUREDNESS.

As the correlations and regressions show, many more useful consumer-related variables emerge for the new SELF ASSURANCE trait index than for FEMININITY. FEMININITY alone seems to have few such correlates: it shows both small explained variance and only a few different correlates in both cohorts. On the other hand, the MASCULINITY index, reconsidered as SELF-ASSURANCE, even without sex traits, is quite relevant to consumer behavior because of the high variance explained and many correlates.

Past sex role research, in the light of the study findings, can now be viewed from a different perspective. Bem's typologies used in a consumer behavior context seem inapplicable. The difference between FEMININE (high femininity and low masculinity scores) and ANDROGYNY (high femininity and high masculinity) simply boils town to the difference in Self-Assurance scores. The difference between ANDROGYNY and MASCULINE (low femininity and high masculinity) depends mainly on femininity scoring. Since FEMININITY is relatively independent of consumer behavior variables, it is not surprising that few differences between the Androgynous and Masculine types have been reported.

Our findings seem to shed light on the problems associated with interpretation of Androgyny. If Androgyny really means a mix of high FEMININITY and high SELF-ASSURANCE, then it is not a true sex-role self-concept, as Bem's original research implies. The differences between FEMININITY and ANDROGYNY might be differences in self-assurance rather than sex-role, and the lack of differences between MASCULINITY and ANDROGYNY might reflect limited differences between high and low FEMININITY trait index scores.

Another implication is that unlike the FEMININITY trait-index which, though appealing, is not useful for marketing purposes, the new measure of SELF-ASSURANCE shows great promise. It has high reliability (ALPHA >.88), and can be used to identify potential innovators in the marketplace.

While full implications of the self-assurance measure require further study, some current fashion trends provide an example of the self-assured woman who considers herself feminine. The apparent paradox of the declining interest in mannish styles and fabrics at the same time as women are increasingly entering the formerly purely masculine world of career commitment makes sense, if one reinterprets self-assuredness as incorporating, rather than denying, femininity. The trend away from "menswear styling" (Harper's Bazaar, July 1985, p. 160), in fact, seems to be spreading in the mit-1980's from the innovative few to the masses. Liz Claiborne often considered the most important designer for the large middle-class and middle-price market, proposes to take women out of "neat little suits that erase the fact that they're women" in Fall 1985 (Harper's Bazaar, June 1985, p. 129).

The creators of promotional appeals might thus take note of the femininized self-assured woman: images of confident women can, for example, be shown in highly romantic settings.

Thus social changes have culminated in reevaluation as feminine of "Self-Assuredness" traits which a decade ago were judged masculine. This shift explains why positive relationships between FEMININITY and SELF-ASSURANCE traits have been so clearly established in this study. It also explains why the Baby-Boomer cohort shows no correlation between SELF-ASSURANCE and self-ascribed "masculine." To some extent, this study confirms that the sexual revolution has won a major battle: women who are aggressive, forceful, competitive, and ambitious view themselves as not losing one bit of their femininity!




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Benny Barak, Hofstra University
Barbara Stern, Kean College of New Jersey


NA - Advances in Consumer Research Volume 13 | 1986

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