lido woman who enter male dominated fields

Prévia do material em texto

American Educational Research Journal 
Summer 1979, Vol. 16, No. 3, Pp. 285-293 
Women Who Enter Male-dominated Fields of 
Study in Higher Education 
SAMUEL S. PENG 
Westat, Inc. 
Rockville, Maryland 
and 
JAY JAFFE 
Research Triangle Institute 
Research Triangle Park, N. C. 
Using data drawn from the National Longitudinal Study of the High 
School Class of 1972, this study examined 16 variables classified into 
categories of family background, high school experience, academic 
ability, life-goal orientations, and extent of education planned that 
might influence women's entry into male-dominated fields of study in 
higher education. Results indicate that women in male-dominated 
fields have higher academic ability and more course work in science 
and mathematics in high school, and that they are more work-oriented 
than women in traditional fields. Results also indicate that family 
influence on women's entry into male-dominated fields is not signifi-
cant. 
It is well-recognized that women are underrepresented in science and 
engineering careers. Although approximately equal proportions of women 
and men are now entering post-secondary educational institutions (Peng, 
1977), the career fields women enter continue to be those traditionally 
dominated by women, such as education and nursing. Between 1972 and 
The work upon which this publication is based was performed at Research Triangle Institute 
under Contract No. OEC-0-73-6666 with the National Center for Education Statistics of the 
Department of Health, Education, and Welfare. The opinions expressed in this paper, however, 
do not necessarily reflect the position on policy of the NCES, and no official endorsement by 
the NCES should be inferred. 
The authors are grateful to two anonymous reviewers as well as Dr. Andrew Kolstad from 
the NCES and Dr. Bruce Eckland from University of North Carolina at Chapel Hill for their 
comments on a previous version of this paper. 
285 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net
Camilla Oliveira
Realce
Camilla Oliveira
Realce
Camilla Oliveira
Realce
PENG AND JAFFE 
1975 less than 10 percent of the doctorates earned in scientific fields were 
granted to women (McCarthy & Wolfe, 1975). Although first-year college 
women are now more likely to choose careers traditionally dominated by 
men than were women ten years ago, the differences in career choice between 
men and women have not been substantially reduced; for the most part, the 
same pattern of changes in career choice holds for both men and women 
(Peng & Talbert, Note 3). In 1961, the Project TALENT data showed that 
a total of 56% men compared to 21% women entered the fields of physical 
sciences, biological sciences, business, and engineering (Flanagan & Cooley, 
1966). In 1972, the difference between men and women in these fields was 
still 35 percentage points, although the proportion of women students in 
these fields has increased to 26% compared to 61% men (Peng & Talbert, 
Note 3). 
Why does the phenomenon of sex differences in career choice persist? The 
question has been addressed by several researchers (e.g., Alexander & 
Eckland, 1974; Featherman & Hauser, 1976; Zellner, 1973). Although the 
studies have speculated about such possible determinants as early stereotyp-
ing, peer influences, aptitudes, the absence of role models, parental expec-
tations, and a number of other family and social factors, they have not 
systematically investigated the network of multiple factors as students move 
from high school into college. 
This study was, therefore, designed to examine multiple factors that may 
influence the entry of women into male-dominated fields as they move from 
high school into college. In particular, the study examined the direct and 
indirect relationships of family background characteristics, high school 
experience, academic ability, and plans and attitudes with the choice of 
male-dominated fields among college women students. The results will help 
to answer such questions as: What types of women defy strong sex-role 
stereotypes by entering male-dominated fields? Are they different from those 
women in traditional roles in their life goals? Do they come from families of 
different backgrounds, or do they graduate from different high school 
curricular programs? 
METHOD 
The Data Base 
The data were drawn from the National Longitudinal Study of the High 
School Class of 1972 (NLS). NLS seeks to discover what happens to young 
people upon leaving high school, as measured by their subsequent educa-
tional and vocational activities, plans, aspirations, and attitudes, and to relate 
this information to their prior educational experiences and personal and 
biographical histories. A detailed description of the sample, instruments, and 
data collection procedures can be found in the NLS Data File Users Manual 
(Levinsohn, Henderson, Riccobono, & Moore, 1978). 
286 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net
Camilla Oliveira
Realce
Camilla Oliveira
Realce
WOMEN IN MALE-DOMINATED FIELDS 
In the NLS first followup survey of the participants, some 9,276 students 
(4,747 men and 4,525 women) entered either 2-year or 4-year institutions by 
the fall of 1972. However, because of missing data on one or more variables 
used in the present study, only about 48 percent of the original sample 
remained in the final analysis (391 women in male-dominated fields; 1,784 
women in other fields; 1,082 men in male-dominated fields, and 1,151 men 
in other fields). Although the remaining sample is sufficient for analysis, 
and no systematic bias in terms of background data is significantly intro-
duced by the reduction of sample, it does preclude testing the interaction of 
sex and ethnicity since the number of ethnic minorities is too small for 
reliable estimates. 
Variable Measurement 
Sixteen variables, classified in six categories, are involved in the study. 
1. Family Background. This category includes four variables: (a) father's 
education, (b) mother's education, (c) father's occupation, and (d) mother's 
occupation. Information regarding parents' education level provided by the 
respondents in their senior year in high school were coded as follows: doesn't 
apply = 1; did not complete high (secondary) school = 2; finish high school 
or equivalent = 3; adult education program = 4; business or trade school = 
5; some college = 6; finish four-year college = 7; attended graduate or 
professional school but did not attain a degree = 8; and obtain a graduate or 
professional degree = 9. The occupational variable was coded as follows: 
professional (e.g., accountant, dentist, physician, engineer, lawyer, scientist) 
= 1; and other (non-professional) = 0. 
2. High School Experience. This was indicated by (a) curricular program, 
(b) total number of science courses, and (c) total number of math courses. 
Curricular program, reported by the respondent, was divided between aca-
demic (i.e., college preparatory program), coded 1, and general and voca-
tional-technical programs, coded 0. The total science and math courses was 
the actual numbers of these courses as shown in the high school record. 
3. Academic Ability. The category includes scores on four standardized 
tests: (a) Vocabulary, (b) Reading, (c) Letter Groups, and (d) Mathematics. 
Each test was standardized to a mean of 50 and a standard deviation of 10. 
These tests were administered in school in the base-year survey. 
4. Life Goals. The category includes three scales developed on the basis of 
the results of a factor analysis of goal-related items in the base-year survey 
(Dunteman, Peng, & Holt, Note 1). Each scale has three items, with responses 
ranging from "not important" (assigned a value of 1) to "very important" 
(a value of 3): Work scale: (a) being successful in my line of work; (b) having 
lots of money;and (c) being able to find steady work. Community scale: (a) 
being a leader in my community; (b) being able to give my children better 
opportunity than I have had; and (c) working to correct social and economic 
inequalities. Family scale: (a) finding the right person to marry and having 
287 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net
PENG AND JAFFE 
a happy family life; (b) living close to parents and relatives; and (c) getting 
away from this area of the country (scored in opposite direction). Scale score 
is a simple average of item responses. 
5. Educational Plans. A single variable, indicated by the respondent during 
the senior year in high school, was: less than high school = 1; high school 
= 2; some vocational-technical education after high school = 3; junior 
college = 4; four-year college = 5; graduate school = 6. 
6. Male-Dominated Fields. The source data for this variable was the 
student's self-response to a question regarding 16 categories of college majors 
in October 1972 in the NLS first followup survey. For purposes of the 
present study these categories were divided into traditionally male-domi-
nated fields of study, and other fields (including the undecided). The male-
dominated fields were biological sciences, business, engineering, physical 
sciences, and math. The divisions were coded 1 and 0, respectively. 
ANALYSIS AND RESULTS 
Path analysis was used to examine a general model of hypothesized direct 
and indirect relationships (see Figure 1). The coefficient of determination 
(R2) for the model is very low, .06 for women and .09 for men, indicating the 
complexity of the process and the weak "explanatory" power of the model. 
Thus the prime import of the findings resides in the within-category infor-
mation (see Tables I and II). 
FIGURE 1. General model for the study of the entry into male-dominated fields 
Note. Categories of variables are defined in the text. 
1. Family 
Background 
Life goals 
Entry into 
male-dominated 
field 
238 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net
TABLE I 
Correlation Coefficients 
FE ME FO MO HSP TS TM VOC RD LG MT WS CS FS EP MDF 
Father education (FE) 54 56 21 16 10 11 28 24 19 24 - 1 0 - 1 0 -09 23 03 
Mother education (ME) 51 32 47 15 07 08 24 21 17 19 - 0 8 -10 -08 16 03 
Father occupation (FO) 53 34 19 09 06 08 15 14 10 14 - 0 8 -10 -07 16 02 
Mother occupation (MO) 21 50 20 05 02 03 08 06 05 05 - 0 4 -04 -05 05 -05 
High school program (HSP) 20 17 11 06 37 36 34 36 38 47 - 0 8 -08 -02 33 06 
Total sciences (TS) 07 06 02 06 31 48 25 29 27 38 -07 -07 -02 23 13 
Total math (TM) 09 06 04 02 35 49 19 24 31 42 - 0 2 -07 03 21 16 
Vocabulary (VOC) 26 23 15 11 37 21 21 63 42 51 - 1 8 -19 - 1 0 30 03 
Reading (RD) 22 20 13 09 36 20 24 68 51 59 - 1 9 -19 -08 31 08 
Letter groups (LG) 20 17 09 06 34 20 22 44 51 67 - 0 8 -17 -01 27 12 
Mathematics (MT) 21 18 14 06 46 31 40 56 62 64 - 1 4 -20 -03 31 17 
Work scale (WS) - 1 2 -11 -07 - 0 4 - 1 2 - 0 3 - 0 3 - 2 2 -21 -17 -19 24 25 -03 02 
Community scale (CS) - 1 2 - 0 8 - 0 9 00 -05 -01 - 0 2 - 1 6 - 1 4 - 1 4 -15 26 20 02 08 
Family scale (FS) -07 - 0 6 -05 - 0 4 -03 -05 - 0 2 -07 - 0 5 01 - 0 0 16 08 - 0 4 -07 
Educational plans (EP) 19 19 12 13 30 19 23 26 24 16 25 - 0 4 07 -03 01 
Male-dominated fields (MDF) 02 00 03 03 03 16 13 02 05 06 09 11 03 -03 -03 
Note. Decimal points are omitted; the lower triangle matrix is for women (n = 2175), and the upper triangle matrix is for men (n = 2233); and any y > 
.04 is significant at the .05 level. 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net
TABLE II 
Standardized Regression Coefficients for the Model of the Entry into Male-dominated Fields 
Dependent variable 
Independent variable 
Dependent variable 
FE ME FO MO HSP TS TM VOC RD LG MT WS CS FS EP R2 
High school program (HSP) 11* 
13* 
09* 
05 
- 0 1 
- 0 1 
- 0 2 
- 0 1 
03 
02 
Total sciences (TS) 02 
05* 
- 0 3 
- 0 1 
- 0 3 
- 0 1 
06* 
- 0 0 
26* 
32* 
07 
11 
Total maths (TM) 04 
04 
- 0 3 
02 
- 0 1 
02 
00 
-01 
35* 
32* 
12 
11 
Vocabulary (VOC) 14* 10* 00 - 0 0 20* 09* 06* 13 
18* 11* - 0 0 - 0 2 18* 12* 00 14 
Reading (RD) 07* 11* 02 - 0 1 16* 04 12* 10 
12* 06* 03 - 0 2 18* 13* 03 12 
Letter groups (LG) 07* 08* 03 - 0 2 13* 06* 09* 07 
08* 04 01 - 0 2 22* 08* 13* 14 
Mathematics (MT) 03 06* 06* - 0 4 20* 09* 30* 23 
09* 05* 03 - 0 3 26* 16* 21* 27 
Work scale (WS) - 0 3 -06* -01 02 - 0 3 02 05 - 0 8 * -07* - 0 1 - 0 7 * 05 
-02 - 0 4 - 0 3 02 - 0 3 - 0 5 * 08* -12* -09* 03 - 0 2 05 
Community scale (CS) -08* - 0 1 - 0 3 04 03 01 04 06* - 0 3 - 0 4 - 0 8 * 04 
-06* - 0 2 - 0 4 .00 03 02 02 - 0 8 * -08* - 0 5 * - 0 5 05 
Family scale (FS) -08* - 0 0 -02 - 0 3 01 - 0 5 - 0 1 -07* - 0 4 06* 05 02 
-01 - 0 3 -05* - 0 2 00 - 0 4 06* -12* - 0 4 01 08* 03 
Educational plans (EP) 08* 05* 00 06* 17* 03 11* 11* 04 03 02 01 10* -04 17 
09* 02 05 00 15* 08* 05* 12* 09* 04 05* 04 13* -05* 20 
Entry of male-dominated fields - 0 0 - 0 4 - 0 0 04 - 0 4 18* 01 - 0 6 * 05 03 05* 05* -04* - 0 3 09* 06 
(MDF) -01 05* 02 -09* - 0 1 13* 09* - 0 8 * 02 - 0 0 12* 14* - 0 8 * -01 -04* 09 
Note. Decimal points are omitted; * is significant at the 05 level: upper entries are for women; lower entries are for men; and the sample size for the analysis was women—2175; 
men—2233, 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net
WOMEN IN MALE-DOMINATED FIELDS 
Family Background 
Both father's and mother's education and occupation appear to have no 
"impact" on (or to be not directly related to) women's entry into the 
traditionally male-dominated fields. However, parents' education is posi-
tively related to women's enrollment in the high school academic (i.e., college 
preparatory) programs, higher test scores, and higher educational plans 
which, in turn, have positive relationships with women's entry in the male-
dominated fields. 
It should be noted, however, that among male students, mother's education 
and occupation have a significant direct relationship with the entry into the 
male-dominated fields. Reasons for the negative relationship of mother 
occupation with the entry into these fields are unknown. 
High School Experience 
For both men and women, high school curricular program is not related 
to the entry into male-dominated fields. However, it is related to science and 
mathematics course work in high school and test scores, probably reflecting 
the fact that more science and mathematics courses are offered in college 
preparatory (academic) programs. 
Total number of science courses taken in high school is related to both 
women's and men's entry into male-dominated fields. This relationship is 
still significant after other variables in the model are controlled. Based on 
the standardized regression weight, this variable appears to be the most 
important predictor of women's entry into men's fields. 
The number of mathematics courses taken in high school is significantly 
related to entry in male-dominated fields for both men and women. However, 
when other variables in the model are simultaneously considered, the 
relationship is no longer significant among women, even though it remains 
so for men. This may be due to the specific field chosen within the set of 
fields of study included as male-dominated fields; and further research may 
uncover relationships between mathematics preparedness and specific fields. 
Academic Ability 
Higher scores on Reading and Letter Groups are related to women's and 
men's entry into the male-dominated fields. The relationships, however, are 
weak when other variables are considered. Vocabulary test score has a direct 
negative relationship with the entry into the male-dominated fields for both 
men and women. Reasons for thisrelationship are unknown. One can 
speculate that the male-dominated fields do not require high vocabulary 
skills or are more attractive to persons with weaker vocabulary skills after 
other variables are considered. 
High achievement on mathematics is an important predictor in women's 
entry into male-dominated fields, supporting previous findings that a poor 
291 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net
Camilla Oliveira
Realce
Camilla Oliveira
Realce
Camilla Oliveira
Realce
Camilla Oliveira
Realce
Camilla Oliveira
Realce
Camilla Oliveira
Realce
PENG AND JAFFE 
preparation in mathematics skills may hamper many women from entry into 
men's fields (Fox, Fenneman, & Sherman, Note 2). 
Life Goals 
Women in the traditionally male-dominated fields have higher scores on 
the work scale and lower scores on the community and the family scales 
than women in other fields after other variables are considered. This finding 
suggests that women in men's fields are more work-oriented. The relationship 
of work and community goals to men's choice of traditional male fields are 
similar and much more marked. The finding that the value of work orienta-
tion is strongly related to choice of male-dominated career goals is consistent 
with the greater prestige and financial reward associated with these jobs; 
and the cultural expectations placed upon men predict these values most 
strongly for the majority of men who do choose to pursue this type of success 
(i.e., success orientation). 
Educational Plans 
The nature of further educational planning is an important predictor of 
the entry into male-dominated fields for women but not for men. This may 
reflect the fact that male-dominated fields are more likely than other fields 
to require four-year college or advanced education. It may also reflect the 
fact that there is little variability on the plans variable for men. 
SUMMARY 
The data show that high school course work, academic ability, success 
orientation, and educational plans are important predictors for women's 
entry into male-dominated fields. The fact that high school course work is 
also an important predictor for men suggests that these courses are probably 
the basic prerequisites or characteristics for entry into male-dominated fields 
for all aspirants. 
REFERENCE NOTES 
1. DUNTEMAN, G. H., PENG, S. S., & HOLT, M. M. Composite score analysis: Ability index, 
SES index, some psychological and educational construct scales. A technical report from 
Research Triangle Institute, NC to the National Center of Education Statistics, 1975. 
2. Fox, L. H., FENNEMAN, E., & SHERMAN, J. Women and mathematics: Research perspective 
for change. NIE Papers in Education and Work: Number 8, National Institute of Education, 
1977. 
3. PENG, S. S., & TALBERT, R. J. Sex differences in career orientations. Paper presented at the 
annual meeting of AERA in Toronto, 1978. 
REFERENCES 
ALEXANDER, K. L., & ECKLAND, B. K. Sex differences in the educational attainment process. 
American Sociological Review, 1974, 39, 668-682. 
292 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net
Camilla Oliveira
Realce
Camilla Oliveira
Realce
Camilla Oliveira
Realce
Camilla Oliveira
Realce
Camilla Oliveira
Realce
WOMEN IN MALE-DOMINATED FIELDS 
FEATHERMAN, D. L., & HAUSER, R. M. Sexual inequalities and socioeconomic achievement in 
the U.S., 1962-1973. American Sociological Review, 1976, 41, 462-483. 
FLANAGAN, J. C , & COOLEY, W. W. Project TALENT: One-year follow-up studies. Pittsburgh: 
American Institute for Research, 1966. 
LEVINSOHN, J. R., HENDERSON, L. B., RICCOBONO, J. A., & MOORE, R. P. National Longitudinal 
Study: Base year, first, second, and third follow-up data file users manual. Research Triangle 
Park, N.C.: Research Triangle Institute, 1978. 
MCCARTHY, J. L., & WOLFE, D. Doctorates granted to women and minority group members. 
Science, 1975, 189 (4206), 856-859. 
PENG, S. S. Trends in the entry to higher education: 1961-1972. Educational Researcher, 1977, 
7(6), 15-19. 
ZELLNER, H. Discrimination against women, occupational segregation in the relative wage. 
American Economic Review, 1972, 62 (2), 157-176. 
AUTHORS 
SAMUEL S. PENG, Westat, Inc., 11600 Nebel St., Rockville, MD 20852 
JAY JAFFE, Research Triangle Institute, Research Triangle Park, NC 
293 
 at UNIVERSITY OF SASKATCHEWAN LIBRARY on June 20, 2015http://aerj.aera.netDownloaded from 
http://aerj.aera.net